{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"17e9033f-5f4e-43a7-8232-b69ebe51130b","company_id":"01b03876-5b01-47ab-82b9-696293e861b9","title":"Senior Machine Learning Engineer","slug":"senior-machine-learning-engineer-4c7e0c3b","description":"Who we are \n Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. \n Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. \n About the role: \n Safety AI builds the ML and computer vision systems behind Samsara's AI dash cameras which enable real-time driver alerts, risk signals, and coaching insights running on millions of edge devices and the cloud. \n This role owns what happens after training: building the resilient, low-latency ML backend systems that turn static model artifacts into high-throughput, cloud-scale safety features. \n You will partner closely with applied scientists, firmware and full-stack engineers, and product managers and you will build the ML APIs, data pipelines, and evaluation infrastructure that let Safety AI models run efficiently at fleet scale, closing the loop from initial integration through rollout monitoring and iteration to a trustworthy, customer-facing signal.  \n This is ML engineering where the stakes are real: rare, high-consequence events, millions of vehicles, and a product where \"it works\" means someone got home safely. Kindly refer to this video . \n This is a remote role open to candidates residing in the US or Canada. \n Technical Charter and Impact: \n \n Own the cloud-side path from model artifact to production system for Safety AI's ML applications. \n Establish practical standards for productionizing models — how they're served, evaluated, versioned, and monitored once they leave applied science. \n Set a high bar for reliability: rigorous evaluation, measurable rollout health, and systems that degrade predictably rather than silently. \n Act as a technical partner to applied scientists, helping translate research outputs into systems that are debuggable, scalable, and cost-efficient in production. \n \n In this role, you will:   \n \n Design Production ML APIs: Architect and maintain reliable, low-latency APIs to integrate Safety AI model outputs directly into cloud applications. \n Build Data Flywheels: Construct scalable pipelines to power continuous model iteration, backtesting, shadow and online evaluation, enabling fast and safe deployments. \n Optimize \u0026 Serve Artifacts: Productionize model artifacts handed off by applied scientists, optimizing serving logic and fine-tuning models for platform-specific workloads. \n Petabyte-Scale Operations: Process high-volume camera and sensor telematics data to support model execution, backtesting, and automated dataset curation. \n Monitor \u0026 Maintain Rollout Health: Build systems to track model drift, precision/recall, and latency regressions in production, ensuring predictable failure modes and closed-loop data feedback. \n Cross-Functional System Integration: Partner with firmware and platform teams to optimize edge-to-cloud model execution, balancing latency, throughput, and infrastructure cost. \n Product Collaboration: Work with product managers to translate safety requirements into scalable technical architectures. \n Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices. \n \n Minimum requirements for the role: \n \n 6+ years of experience as a Machine Learning Engineer or similar role, with a track record of shipping models in production. \n Strong proficiency in one or more common languages (e.g., C++, Golang, Java, Python, Scala). \n Proficiency with common ML tools (e.g. Ray/Ray Serve, MLflow, Grafana, Pytorch, Spark, etc). \n Experience deploying and iteratively refining models using real customer feedback loops. \n Comfort with full-stack/backend development — you understand the data structures and dependencies underneath your models. \n BS or MS in Computer Science or a related quantitative field. \n \n An ideal candidate also has: \n \n Ph.D. in Computer Science or a quantitative discipline (e.g., Applied Math, Physics, Statistics). \n Experience with containerization (Docker, Kubernetes), CI/CD pipelines, and infrastructure-as-code frameworks. \n Experience de","salary_min":170170,"salary_max":286000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","computer-vision","pytorch","fine-tuning","machine-learning"],"apply_url":"https://www.samsara.com/company/careers/roles/8055245?gh_jid=8055245","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-10T13:25:43Z","expires_at":"2026-10-10T13:35:01.78704Z","created_at":"2026-09-10T13:35:01.921729Z","updated_at":"2026-09-10T13:35:01.921729Z","company_name":"Samsara","company_slug":"samsara","company_logo_url":"https://www.google.com/s2/favicons?domain=www.samsara.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/17e9033f-5f4e-43a7-8232-b69ebe51130b"},{"id":"8a11e24b-763c-4a00-9223-55e73fc8f9c0","company_id":"a0000000-0000-0000-0000-000000000001","title":"Performance Engineer, Inference Engine","slug":"performance-engineer-inference-engine-c9c1c8d4","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n Performance Engineer, Inference Engine\n About the Role\n Anthropic's inference engine is the software between the accelerator kernels and the routing layer. It manages the entire token path in between: batching requests, laying the model out across chips, managing memory for weights and activations, coordinating every forward pass, and managing model state across requests. Built in-house, it runs on all of our accelerator platforms, serving Claude to millions of users and running our research workloads.\n You will work on building and optimizing this system at Anthropic scale: improving throughput, cost, reliability, and latency across all accelerator and cloud platforms. You are intimately familiar with the hardware and bandwidth numbers (FLOPs, HBM, PCIe, RDMA, network links, etc.) and can model a problem quickly: where the time and bytes go, and what sets the bound. The role is deeply technical and high-impact, and suits engineers who enjoy working across accelerator programming, high-performance systems that seamlessly coordinate between host and device, and large-scale distributed systems. Familiarity with the transformer architecture is a plus.\n Some example recurring themes:\n \n \n Keep device utilization high. Accelerators should never be waiting due to other overheads.\n \n Reuse instead of recompute. Keep model state cached and reuse it whenever that is cheaper than computing it again.\n \n Measure, model, then change. We build the observability to see where the gaps are, model the impact of potential improvements, deploy them, and go around again, with Claude speeding up every turn of that loop.\n \n Tokens you can trust. Ensuring model quality matters more than efficiency. We build the infrastructure to ensure Claude maintains its intelligence across platforms and over time. \n \n Safety on every token. We work closely with our safeguards and safety teams. The inference engine is the backbone behind our production safety systems, ensuring efficiency without compromising robustness. \n \n Minimum Qualifications\n \n \n A working mental model of LLM inference: how prefill and decode land on an accelerator's compute, memory, and interconnect, and what the host is doing meanwhile\n \n Proven quick learner: ramped fast in deep, unfamiliar systems and shipped consequential changes quickly\n \n Strong systems programming (Rust, C++, or similar), with care for code quality and tests\n \n Analytical about performance: observe and profile first, form a hypothesis, test it, then change the code and measure again\n \n Low ego: ask the naive question, take feedback well, pick up slack outside your job description\n \n Enjoy pair programming (we love to pair!) and care about the societal impacts of your work\n \n Preferred Qualifications\n \n \n Experience inside an LLM serving engine and a sense of where its abstractions strain\n \n GPU/Accelerator programming\n \n OS internals\n \n Language modeling with transformers\n \n Experience building an allocator, cache, scheduler, or high-bandwidth transport\n \n Fluency in Rust\n \n Experience making systems reproducible: determinism, replay, property-based tests\n \n \n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $350,000 — $850,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself premature","salary_min":350000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["distributed-systems","llm","alignment","inference","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5418323008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T23:09:53Z","expires_at":"2026-10-10T13:30:31.379391Z","created_at":"2026-09-10T13:30:31.557342Z","updated_at":"2026-09-10T13:30:31.557342Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8a11e24b-763c-4a00-9223-55e73fc8f9c0"},{"id":"8ab1f26e-10a9-4bf0-b1f7-187e57c36cba","company_id":"cec3f1a8-c7e9-4ff6-a22d-19edaf0e2b25","title":"Security Engineer, Threat Intelligence","slug":"security-engineer-threat-intelligence-d8832026","description":"ABOUT FLUIDSTACK\n\nWe exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it. \n\n\nWe're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.\n\n\nWe hire people who care deeply about this problem space. If that is you, please apply!\n\n\n\n\nHOW WE OPERATE\n\n - Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role.\n\n - Insane urgency. We drive everything forward as fast as possible.\n\n - Reason from first principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.\n\n - Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.\n\n - Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world.\n\n\n\n\nHOW WE OPERATE\n\n - Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.\n\n - Velocity. We drive everything forward as fast as possible.\n\n - First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.\n\n - Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.\n\n\nTHE SECURITY TEAM\n\nExamples of key problems the team is working on\n\n - You're securing the frontier of AI. The model weights training on our infrastructure are the most valuable and most targeted artifacts in technology, and we're standing up the compute to hold them faster than anyone ever has. A breach isn't a leak, it's the frontier walking out the door.\n\n - Build the entire security program from scratch. Most leaders inherit someone else's system and spend a career patching it. Here you own it end to end, bare metal to boardroom, as we scale across continents.\n\n - Your threat surface is measured in gigawatts. The customers running on our infrastructure are building the most consequential technology in human history, and being responsible for the physical and logical security of that work makes everything else feel small.\n\n\nROLE SCOPE\n\n - Track the nation-state and advanced criminal actors most likely to target frontier AI infrastructure, and turn their tooling, infrastructure patterns, and tradecraft into intelligence that changes what the program detects and hunts for.\n\n - Build and run the pipelines that collect, enrich, and correlate indicators, then push them into the detection and agentic triage stack so intelligence becomes operational instantly.\n\n - Drive intelligence-led hunts across enterprise, cloud, identity, data center IT, and OT telemetry, and convert findings into high-fidelity detections authored as code.\n\n - Perform hands-on malware, phishing-infrastructure, and attacker-tooling analysis to extract indicators, TTPs, and attribution signals that feed detection engineering and incident response in near real time.\n\n - Curate the inbound intelligence pipeline across commercial feeds, open source, government, and peer relationships, and prioritize what actually matters for the program's threat model.\n\n - Build and maintain the external intelligence-sharing relationships (ISACs, peer AI and cloud security teams, government partners) that keep the program ahead of active campaigns.\n\n\nWHAT WE'RE LOOKING FOR\n\nThe below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would https://jobs.ashbyhq.com/fluidstack/05c2e69c-42f9-4fcb-9cf0-a467aaf98f1c.\n\n - You've tracked specific nation-state or advanced criminal actors as a core part of your job, and you know their tooling, infrastructure, and targeting well enough to anticipate their next move.\n\n - You write production-quality Python (or similar) and have built the automation and data pipelines your intelligence work depended on, end to end.\n\n - You've done hands-on malware, infrastructure, and log analysis to develop and validate your own findings.\n\n - You've authored quality detection logic (YARA, Sigma, or SIEM-native queries) that shipped to production and held up against real adversary activity.\n\n - You've worked shoulder t","salary_min":220000,"salary_max":280000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","security","data-pipeline"],"apply_url":"https://jobs.ashbyhq.com/fluidstack/9068a6c7-6278-4aa3-a968-ffc0e2a2a636/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T21:51:39.167Z","expires_at":"2026-10-10T13:45:49.25615Z","created_at":"2026-09-10T13:45:49.37723Z","updated_at":"2026-09-10T13:45:49.37723Z","company_name":"FluidStack","company_slug":"fluidstack","company_logo_url":"https://www.google.com/s2/favicons?domain=fluidstack.io\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8ab1f26e-10a9-4bf0-b1f7-187e57c36cba"},{"id":"42b8ed9d-a0ae-40e0-93f0-b2e2b7a9f586","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"Senior Product Manager, Asta","slug":"senior-product-manager-asta-15236686","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $115,920 - $173,880, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are:  \n You think like a builder and an advocate at the same time. You can sit with a researcher who's pursuing a novel method and hasn't yet found the words to describe what they need, and translate that into engineering requirements that an engineering team can actually build against. You're comfortable operating at the intersection of infrastructure and science: you don't need to be an ML researcher, but you're genuinely curious about how researchers work, what agentic frameworks make possible, and where the current tooling gets in their way. You know how to turn a fuzzy, ambitious mission into a tactical roadmap with sequenced milestones and clear ownership. You hold a high bar for the experiences and tools already in the hands of our users, because internal researchers and the broader community depend on them being fast, reliable, and compliant, even while you're pushing the frontier of what's next.\n Who We Are:  \n At Ai2, our mission is to develop breakthrough AI that solves the world's biggest problems. We believe the insight needed to get there lives at the intersection of deep scientific AI understanding and the application of AI in common-good domains. This role sits on our Strategic Programs team, which also includes Product Management, Design, and Communications. As a team, we help shape Ai2's strategic vision and accelerate execution of its goals. We are a highly collaborative team with a high bar for excellence, who aren't afraid to question how things have been done in the past to propose changes that drive the organization forward. It's a very exciting time to be part of this team as Ai2 plays a unique role in shaping how AI changes the world.\n Your Next Challenge:  \n You will own the engineering and data frameworks of Asta, Ai2's platform for building agents that advance scientific research. Your users are the researchers and engineers who build on Asta; Ai2's own research teams and the broader AI-for-science community.  Your primary partner will be the Agentic Frameworks and Data engineering team. You'll be one of the first product minds shaping what an agentic platform for science actually looks like.  There's no existing playbook to inherit, so you have the opportunity to define engineering requirements grounded in real researcher workflows, build the roadmap for Asta's agentic framework and its supporting tools, and run the feedback loop that keeps engineering and research in continuous conversation. You'll also own the Semantic Scholar data platform end to end; a knowledge graph of 100M+ papers, and the public APIs that power Asta and science agents. You’ll keep these resources reliable for the millions who depend on it and continue building them into the highest-quality open literature resource in the field.\n In This Role, You Will: \n \n Define Asta engineering requirements by working directly with Ai2 researchers to understand their workflows, translating what you learn into clear, prioritized specifications for the Agentic Frameworks engineering team.\n Help articulate trade offs to help guide the team towards the highest impact priorities and investments.\n Build and sequence the roadmap for Asta's agentic framework and its supporting tools, so that new tools and capabilities compound toward unlocking real scientific advancements.\n Create and run a continuous feedback loop between engineering and research, so that researchers’ needs surface early and shape the roadmap, and so that new capabilities get back in front of researchers quickly.\n Drive adoption of Asta's tools among Ai2's own researchers, so that our internal science runs on the platform we ship to the world.\n Project manage and drive execution across Asta engineering workstreams: track progress against the roadmap, unblock dependencies, and keep engineering and research aligned on priorities and tradeoffs.\n Own the Semantic Scholar platform end to end: data platform and public APIs. Balancing reliability for millions of users with the roadmap to rebuild the platform.\n Own Ai2's benchmarking strategy for scientific agents: set the direction for AstaBench, our public benchmark suite, and define which evaluations Ai2 standardizes on internally, with partners, and for the broader AI research community\n Own regulatory and governance compliance for these products, including data subject rights such as right to access and right to be forgotten, partnering with legal as needed.\n Represent the researcher and developer perspective in engineering planning, and represent engineering constraints and tradeoffs back to research and leadership.\n Contribute to how ","salary_min":115920,"salary_max":173880,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["robotics","agents","llm","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/8178819","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T21:38:29Z","expires_at":"2026-10-10T13:48:45.82775Z","created_at":"2026-09-10T13:48:45.94798Z","updated_at":"2026-09-10T13:48:45.94798Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/42b8ed9d-a0ae-40e0-93f0-b2e2b7a9f586"},{"id":"aea83272-45e2-4f96-9714-503579e71ec3","company_id":"00efdc26-b22e-49e8-b7e8-3e24e6bea23e","title":"Founding Product Engineer","slug":"founding-product-engineer-3ffcf973","description":"Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.\n We are building a new Physical AI product line at Netradyne — a vision-based platform that monitors activity across physical environments and surfaces safety risks in real time. This is founding-team work, and we're hiring generalists who are excited about building something new. \n  \n A Founding Product Engineer owns problems end-to-end — from an edge device, through the cloud platform, to the surface a safety manager touches — and moves fluidly between them depending on what the product needs that week. You'll naturally lean toward platform/infrastructure or toward product/experience based on your strengths, but you're expected to have working range across both, not a hard boundary between \"backend team\" and \"frontend team.\" You talk to customers directly, turn what you hear into what gets built, and take it the rest of the way to shipped. \n  \n Essential Functions: \n Platform \u0026 infrastructure (lean here if that's your strength): \n \n Cloud ingestion and storage  — real-time event streaming, time-series and event storage, the data model for safety events and metrics. \n Multi-tenancy, identity, and access control  — multiple customers, multiple sites per customer, role-based access control, authentication and SSO. \n Infrastructure and DevOps  — AWS, containerized deployments, CI/CD, and monitoring across the edge and cloud stack. \n \n Product \u0026 experience (lean here if that's your strength): \n \n Operations dashboard  — real-time event feed, alert detail with video clips, site map, zone-violation tracking, risk summaries. \n Compliance analytics  — trend reporting, time-based comparisons, exportable reports for safety and operational record-keeping. \n Operator scoring and coaching workflow  — worker/operator safety scoring, coaching queue, session tracking and completion. \n \n Shared, regardless of lean: \n \n Agent layer / agentic features  — the orchestration layer and conversational/agentic surfaces over safety data (alert triage, auto-coaching drafts, summarization), built on managed services or internal modules where they fit. \n Rapid iteration with real customers  — ship fast, instrument usage, work directly in the field, run pilots alongside live deployments. \n \n Qualifications: \n What we're looking for: \n \n Systems thinking  — you can reason about a problem end-to-end, from device to cloud to the person using it, and make sound calls with incomplete information. \n Dynamic range  — you move between an infra problem, a product/UX problem, and a customer conversation within the same week without needing to be re-anchored each time. You don't default to the one lane you're most comfortable in. \n Bias to action, full ownership  — given an ambiguous problem, you scope it, build it, ship it, and measure it, without waiting to be told the next step. \n Direct customer experience  — you've worked directly with customers or end users to shape what gets built, not just built to a spec handed down. \n \n Baseline technical range: \n \n Full-stack comfort: a modern backend language (Go, Python, Java) and, depending on lean, either cloud infrastructure (AWS, containers, CI/CD, distributed/event-driven systems) or modern frontend (TypeScript/JavaScript) and data-dense real-time UI (dashboards, event feeds, video, timelines). \n Experience designing or working within multi-tenant systems with role-based access control. \n Fluent with AI-assisted development tools (Claude Code, Codex, Cursor) as part of your day-to-day workflow. \n 7+ years of software engineering experience. We'd rather have someone with less tenure and real range than more tenure in one narrow lane. \n \n Nice to have: \n \n Agent orchestration or workflow engines (e.g. Temporal); managed identity platforms (WorkOS, Auth0, Clerk). \n Data pipelines at scale (Spark/PySpark, time-series); high-volume IoT or sensor data. \n Building or integrating AI agent features (tool use, conversational interfaces, LLM-powered surfaces) — a strong differentiator. \n Safety, operations, or compliance software experience. \n \n Education: \n \n Bachelor's degree in Computer Science, Engineering, or a related technical field. \n San Diego Pay Range\n $140,000 — $190,000 USD \n We are committed to an inclusive and diverse team. Netradyne is an equal-opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.\n If ","salary_min":140000,"salary_max":190000,"location":"San Diego, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","payments","llm","computer-vision","cloud","data-pipeline"],"apply_url":"https://www.netradyne.com/company/careers?gh_jid=4732434005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T21:14:27Z","expires_at":"2026-10-10T13:49:30.031638Z","created_at":"2026-09-10T13:49:30.151732Z","updated_at":"2026-09-10T13:49:30.151732Z","company_name":"NetraDyne","company_slug":"netradyne","company_logo_url":"https://www.google.com/s2/favicons?domain=netradyne.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/aea83272-45e2-4f96-9714-503579e71ec3"},{"id":"2d764a21-548d-4995-b28e-a419ab251185","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, ML Inference Path","slug":"staff-software-engineer-ml-inference-path-b64fb22d","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role: \n The Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML based safety systems. We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch. And we build for scale: serving thousands of ML classifiers, for all requests on the token generation path, and for every platform Claude runs on -- 1P, Bedrock, Vertex, and beyond.\n We’re growing the team and looking for engineers who have deep expertise in productionizing ML systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale. And your tooling and infrastructure will be used for every model launch, which are becoming more complex, and more frequent.\n Responsibilities: \n \n Design and build scalable ML infrastructure to support real-time safety deployments across our classifier and model ecosystem\n Build monitoring and observability tools to track classifier performance, data quality, and system health for safety-critical applications\n Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems\n Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards\n Implement automated testing, deployment, and rollback systems for ML models in production safety applications\n Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs\n Contribute to the development of internal tools and frameworks that accelerate safety research and deployment\n \n You may be a good fit if you: \n \n Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX\n Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads\n Have built automated or self-service deployment pipelines and eval infrastructure allowing researchers to roll out classifiers and models independently\n Have implemented A/B testing frameworks and experimentation infrastructure for ML systems\n Are results-oriented, with a bias towards reliability and impact in safety-critical systems\n Enjoy collaborating with researchers and translating cutting-edge research into production systems\n Care deeply about AI safety and the societal impacts of your work\n \n Strong candidates may also have experience with: \n \n Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment\n Working with large language models and modern transformer architectures\n Developing monitoring and alerting systems for ML model performance and data drift\n Experience in trust \u0026 safety, fraud prevention, or content moderation domains\n Knowledge of privacy-preserving ML techniques and compliance requirements\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to e","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","tensorflow","alignment","distributed-systems","pytorch","inference","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5419869008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T19:19:17Z","expires_at":"2026-10-10T13:30:51.14208Z","created_at":"2026-09-10T13:30:51.32706Z","updated_at":"2026-09-10T13:30:51.32706Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2d764a21-548d-4995-b28e-a419ab251185"},{"id":"8b77ea04-5765-490a-966c-cfd6746b16dd","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, ML Sampling Path","slug":"staff-software-engineer-ml-sampling-path-4534cff4","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role: \n The Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down.\n What you'll do: \n \n Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines.\n Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through.\n Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow.\n Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization.\n \n You may be a good fit if you: \n \n Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation.\n Have a strong foundation in distributed systems: replication, consistency tradeoffs, failure modes, and SLO management under load.\n Design systems for graceful degradation: you plan for a slow dependency, a dropped stream, or a half-rolled-out deploy before it happens, and build so the system degrades predictably instead of failing.\n Have successfully shipped broad or all-encompassing changes to mission critical systems (e.g., database migrations, interface changes, rewrites).\n \n Strong candidates may also have: \n \n 8+ years of industry software engineering experience.\n Familiarity with LLM inference systems and transformer-based models (not required, but a plus).\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit  anthropic.com/careers  direc","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","distributed-systems","llm","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5419868008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T19:17:24Z","expires_at":"2026-10-10T13:30:51.275614Z","created_at":"2026-09-10T13:30:51.446194Z","updated_at":"2026-09-10T13:30:51.446194Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8b77ea04-5765-490a-966c-cfd6746b16dd"},{"id":"7ea105b2-5855-4894-bf6c-9c1516072074","company_id":"2721f049-2cf2-4e3e-82d0-8d8df89c8f90","title":"DIrector of Product, Ecosystem ","slug":"director-of-product-ecosystem-873b5241","description":"About Nebius: \n Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.\n Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.\n Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R\u0026D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R\u0026D.\n The role   \n  \n Nebius builds the infrastructure serious AI teams run on — GPU clusters, inference runtimes, agent development environments, data pipelines — all of it purpose-built for the most demanding AI workloads. What we are now building is the ecosystem function that ensures the best AI companies choose to build on us, integrate with us, and stay.   \n The Director of Product, Ecosystem owns the external view of one or more Nebius platform layers. You will map who matters, engage the targets that count, prototype what a partnership actually looks like on our stack, and translate everything you learn into new platform capabilities and product decisions.   \n You’re welcome to work remotely in the United States .\n Your responsibilities will include:   \n Strategy   \n \n Own the ecosystem map for your platform layer — who matters, what they build, where the gaps are relative to our platform strategy \n Define which companies to engage and why — a prioritized target list with a thesis behind every name\n Translate external landscape signals into concrete build vs. buy vs. partner recommendations for product and exec leadership   \n \n Sourcing   \n \n Lead outbound engagement with founders, operators, and investors across your ecosystem domain \n Build peer-level relationships with AI startup founders — the kind where people call you before they announce anything\n Identify partnership, integration, and M\u0026A targets before they are obvious to the market   \n \n Solutioning   \n \n Prototype integrations between partner products and the Nebius stack — fast, hands-on, and technically sound \n Scope partner architectures against our platform — how does this product actually work on our stack, where does it snap together, where does it break\n Define the technical narrative and reference architecture for each partnership\n Produce working proofs-of-concept that serve as the starting point for product creation — not a requirements doc, a working thing   \n \n Internal   \n \n Work with ISV partners, SI teams, and field teams to scale solution adoption and drive revenue once a solution is ready \n This entire motion — inception, experimentation, prototyping — serves as a pipeline for new platform capabilities and product development\n Bring outside-in frontier signal into the company and help leadership make the right choices on where to invest\n Participate in platform planning as the external voice of the ecosystem   \n \n Platform focus areas   \n Depending on your background and mutual fit, you will own one or more of the following:   \n \n Agentic  — agent frameworks, memory systems, tool integration, orchestration, guardrails \n Managed Inference  — inference runtimes, model routing, optimization tooling, serving infrastructure \n IaaS / Managed Infrastructure  — cloud-native integrations, GPU orchestration, sovereign cloud, enterprise infrastructure \n Data  — vector databases, retrieval systems, data pipelines, labeling infrastructure, synthetic data   \n \n We expect you to have:   \n \n \n \n 8+ years operating across product strategy, business development, and ecosystem or partnership development in AI or infrastructure \n Deep technical fluency in at least one of our platform layer domains — you understand the architecture, the players, and the dynamics from having been close to the work, not just reading about it\n Genuine relationships with AI founders and VCs — people take your call because of who you are, not what company you are calling from\n Experience as a founder, early operator, or investor in AI or infrastructure — you understand how startups make decisions and what they actually need from a platform partner\n Comfort going hands-on — you can prototype an integration, scope a partner's architecture, and produce a working proof-of-concept without waiting for an engineer to do it for you\n Strong written and verbal communication — you can present a partnership thesis to a VP of Product and a Series A founder in the same week and be credible in both rooms\n Comfortable building without a playbook — you create the process, you do not wait for it   \n \n It will be an added bonus if you have:   \n \n Founded or been an ear","salary_min":228000,"salary_max":285000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["embeddings","gpu","data-pipeline","agents","cloud"],"apply_url":"https://careers.nebius.com/?gh_jid=4969276101","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T19:11:38Z","expires_at":"2026-10-10T13:46:21.282226Z","created_at":"2026-09-10T13:46:21.408549Z","updated_at":"2026-09-10T13:46:21.408549Z","company_name":"Nebius","company_slug":"nebius","company_logo_url":"https://www.google.com/s2/favicons?domain=nebius.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7ea105b2-5855-4894-bf6c-9c1516072074"},{"id":"6d70b8ad-5639-41e6-a5f2-fa59a897c577","company_id":"306e45a2-c643-4af1-badb-5343eeb92037","title":"ML Infrastructure Engineer","slug":"ml-infrastructure-engineer-637624a1","description":"About Zipline\n Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. \n Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.\n Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.\n We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.\n About You and The Role  \n As an ML Training \u0026 Inference Infrastructure Engineer on the Data Platform team you will be building and scaling the systems powering our data flywheel.  This person will work at the intersection of autonomy and the infrastructure, owning systems that make ML development faster, reproducible, observable, and safe.\n This role is for a strong software engineer who enjoys the full ML development cycle: data ingestion, processing pipelines, dataset management, distributed training, continuous model integration, evaluation, and deployment.  The ideal candidate has strong production engineering habits and is excited to build infrastructure that helps real autonomous systems improve over time.\n What You'll Do \n \n Build and operate software infrastructure that enables learning algorithms to leverage Zipline’s large-scale (quickly growing!) fleet data.\n Design scalable, maintainable data and ML infrastructure for autonomy teams, including dataset creation, validation, training, evaluation, and deployment.\n Own and improve data pipelines that feed into the ML development loop.\n Identify and mitigate bottlenecks in the ML development cycle, especially around orchestration, performance, and reproducibility to increase the rate at which we can improve and scale the delivery experience.\n \n What You'll Bring \n \n 3+ years of professional software engineering experience, ideally including ML infrastructure, data infrastructure, robotics, autonomy, aerospace, medical devices, or another safety-critical hardware/product environment.\n Strong software engineering practices in Python in a production setting; comfort designing APIs, services, schemas, jobs, and operational workflows.\n Experience building reproducible data pipelines and machine-learning pipelines.\n Experience monitoring data statistics, system performance metrics, pipeline failures, and model/evaluation signals.\n Working knowledge of ML concepts such as datasets, training, evaluation, optimization, statistics, and modern deep learning workflows.\n Generalist mindset and willingness to work across cloud services, data platforms, developer tooling, and embedded/robotics-adjacent constraints.\n Experience with PyTorch or similar ML frameworks.\n Strong ownership, clear communication, and interest in building secure systems for mission-critical workflows.\n Experience with Kubernetes or other container orchestration systems for production workloads.\n Experience with cloud and on-premise production infrastructure, preferably AWS, and infrastructure-as-code tools such as Terraform or CloudFormation.\n \n BONUS POINTS \n \n Experience deploying or evaluating ML systems on real robots, autonomous vehicles, drones, or other hardware products.\n Experience with large-scale training systems, feature stores, data/versioned artifact stores, model registries, or experiment tracking.\n Experience with annotation systems, dataset inspection tooling, or active-learning workflows.\n \n What Else You Need To Know \n The starting cash ranges for this role is $160,000 - $250,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compens","salary_min":220000,"salary_max":250000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","pytorch","healthcare","robotics","data-pipeline","autonomous-vehicles","deep-learning","distributed-systems"],"apply_url":"https://www.zipline.com/open-roles/7989516003?gh_jid=7989516003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T16:31:49Z","expires_at":"2026-10-10T13:39:53.197598Z","created_at":"2026-09-10T13:39:53.336529Z","updated_at":"2026-09-10T13:39:53.336529Z","company_name":"Zipline","company_slug":"zipline","company_logo_url":"https://www.google.com/s2/favicons?domain=www.flyzipline.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6d70b8ad-5639-41e6-a5f2-fa59a897c577"},{"id":"6f319733-11a0-4f1f-b28d-90874831c307","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"AI Editor","slug":"ai-editor-036a3c3b","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $92,880 - $139,320, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are: \n To thrive as an AI Editor at Ai2, you'll bring a blend of sharp editorial judgment and genuine curiosity about how language models work. You have 5+ years of experience as an editor, content strategist, technical writer, or content developer, and you've applied that background to human-in-the-loop AI evaluation, prompt engineering, or model quality assessment. You write and communicate with precision, you enjoy translating fuzzy, high-level guidelines into language a model can act on, and you're comfortable context-switching across partners in Product, Research, and Engineering. You're energized by fast-moving, ambiguous environments and enjoy owning quality end-to-end — from style guide to shipped model behavior.\n Who We Are: \n We are a non-profit AI institute focused on developing foundational AI research and innovation to deliver real-world positive impact through large-scale open models, data, and artifacts (e.g., Olmo , Tulu , Molmo , FlexOlmo ). Balancing academic freedom with corporate-level scale ( read about our new compute cluster here ), Ai2 is uniquely resourced and positioned to deliver high-impact, truly open research. Our team unites the best and brightest scientific, engineering, and editorial minds to explore the potential of truly open AI. Through our efforts, we endeavor to empower academics, researchers, and AI developers more broadly to advance the science of language models, multimodal models, and generative AI.\n If you are passionate about advancing the science of AI through open, rigorous research and believe in accessible AI for the common good, we want to hear from you!\n Your Next Challenge: \n \n Translate complex content and safety policies into prompts and guidelines that models can reliably follow, ensuring alignment with product and research priorities\n Improve model fluency, tone, and quality through human-in-the-loop evaluations and LLM-judge audits\n Develop and apply novel prompting approaches to support feature development and reduce model defects\n Create high-quality alignment data to train and fine-tune models for product-specific use cases\n Identify potential biases or limitations in model outputs and work with research partners on fine-tuning strategies to address them\n Build and maintain quality, style, and tone guidelines, and use user feedback to continually improve model helpfulness\n Become a subject matter expert across sensitive topic areas and content policies relevant to the product\n Partner across Product, Research, and Design to evaluate quality metrics and build scalable reporting systems for continual model improvement\n \n What You'll Need: \n \n Bachelors Degree or 5+ years of equivalent experience as an editor, content strategist, technical writer, or content developer\n Experience with human-in-the-loop AI evaluation, prompt engineering, or AI model quality assessment\n Exceptional written and oral communication skills, with strong editorial judgment\n Strong project management skills and comfort managing workload under tight deadlines or escalated activity\n Deep curiosity about how language models work and a passion for user experience\n Comfort context-switching and partnering at all levels of the organization to deliver results\n \n Preferred:\n \n Experience leading cross-functional teams to deliver products and projects on tight deadlines\n Experience in content creation or copy editing, including online publishing\n Experience working in fast-paced, startup-like environments\n \n Physical Demands and Work Environment: \n The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.\n \n Must be able to remain in a stationary position for long periods of time.\n The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.\n The ability to observe details at close range.\n Can work under deadlines.\n \n A Little More About Ai2: \n Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world’s biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.\n In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:\n \n We are a lea","salary_min":92880,"salary_max":139320,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","robotics","llm","healthcare","generative-ai","research"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/8178700","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T16:19:35Z","expires_at":"2026-10-10T13:48:45.010502Z","created_at":"2026-09-10T13:48:45.183378Z","updated_at":"2026-09-10T13:48:45.183378Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6f319733-11a0-4f1f-b28d-90874831c307"},{"id":"967953a1-9ee5-4b1b-bc67-2472980ae075","company_id":"a0000000-0000-0000-0000-000000000001","title":"Security Engineer, Offensive Security","slug":"security-engineer-offensive-security-3ad63df4","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the Team \n The Security Engineering team's mission is to safeguard our AI systems and maintain the trust of our users and society at large. Whether we're developing critical security infrastructure, building secure development practices, or partnering with our research and product teams, we are committed to operating as a world-class security organization and keeping the safety and trust of our users at the forefront of everything we do.\n What You’ll Do: \n \n Conduct red and purple team engagements simulating advanced threat actors across our cloud infrastructure, endpoints and bare metal deployments.\n Penetration test specific, high value deployments.\n Contribute to AI-assisted security testing tooling and workflows.\n Work cross functionally with other security and engineering teams, particularly on AI-specific attack scenarios.\n Document and present findings to technical and executive audiences, translating attack narratives into actionable risk insights that inform security roadmaps.\n \n Who You Are: \n \n 5+ years of hands-on experience in red teaming and offensive security operations\n Deep expertise in at least two of: macOS security, Linux Security, Cloud security (GCP/AWS/Azure), Kubernetes, CI/CD pipelines\n Track record of discovering novel attack vectors and chaining vulnerabilities creatively\n Experience conducting adversarial simulations against well-defended environments\n Strong engineering skills (Python, Go, or similar)\n Ability to write clear findings that drive action, helping teams understand risk and prioritize fixes\n Collaborative approach, working in close collaboration with the blue team\n \n Strong candidates may also have experience with: \n \n Prior work at organizations with state actor threat models\n Interest in AI safety and how security engineering contributes to responsible AI developments\n Background testing AI/ML systems or agentic workflows\n Familiarity with detection engineering and SIEM/EDR platforms from the defensive side\n Experience with data center security or hardware-based attacks\n \n Deadline to apply: None. Applications will be received on a rolling basis.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $300,000 — $320,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit  anthropic.com/careers  directly for confirmed position openings.\n How we're different \n We believe that the highest-impact AI research will be big science. At Anthropic we work as a singl","salary_min":300000,"salary_max":320000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","alignment","cloud","security"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5418977008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T03:51:37Z","expires_at":"2026-10-10T13:30:42.383977Z","created_at":"2026-09-09T13:30:33.833859Z","updated_at":"2026-09-10T13:30:42.526206Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/967953a1-9ee5-4b1b-bc67-2472980ae075"},{"id":"3098d7fe-9844-4077-87c6-d515093dabf4","company_id":"a0000000-0000-0000-0000-000000000001","title":"Salesforce Developer","slug":"salesforce-developer-e2b7e7c8","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n As a Salesforce Developer at Anthropic, you will design, build, and maintain the Salesforce platform that powers our core customer motions and quote-to-cash business.: This includes automation throughout the Salesforce platform ranging from core sales automation to product catalog and pricing, quoting and approvals, order and contract management, and the handoff to billing and provisioning. You'll work both autonomously and collaboratively across RevOps, Order Management, Legal, Billing Engineering, Deal Desk, Finance and Accounting, and Product to translate pricing and packaging requirements into scalable Apex, Flow, and integration solutions, and to extend our capabilities with custom code where necessary. We are an AI-first systems team, and you'll be expected to use Claude and our in-house AI development tooling as a core part of how you write, review, and ship code, always against our house standards for flexibility, maintainability, and scale.\n Key responsibilities \n \n Develop and maintain Apex (triggers, services, selectors, batch/queueable), Lightning Web Components, and Flow automation following our house Apex standards and trigger framework\n Design and build quote-to-cash infrastructure in Salesforce, including the product catalog and pricing data model, quote and order lifecycle, discount and approval automation, and amendment, renewal, and co-termination flows\n Extend CPQ and expand into agentic selling with custom pricing and quote-calculation logic, quote and order user experiences, and code built against the package's APIs and data model\n Build and own integrations between Salesforce and our billing, provisioning, and finance systems, such as Stripe, Metronome, and NetSuite, directly or via middleware\n Support new product and pricing launches by modeling catalog, SKU, and pricing changes so they can be released quickly and reflected consistently in every downstream system\n Use Claude and our internal AI development tooling as a first-class part of your build and code-review workflow\n Partner with Business Systems analysts and Finance to ensure data-model decisions support downstream bookings, forecasting, and revenue reporting\n Partner with DevOps on release management for your work: sandbox strategy, source control, peer review, and deployment via SFDX/metadata tooling\n Ensure appropriate controls, test coverage, and documentation are in place for an effective control environment, particularly around pricing, discounting, and contract changes\n Operate with ambiguity in a rapidly changing business, resolve problems independently, and propose solutions that scale\n \n Minimum qualifications \n \n Hands-on Salesforce development experience (Apex, SOQL, LWC, Flow) in a production org\n Experience building or extending CPQ and quote-to-cash functionality in Salesforce (Salesforce CPQ, Revenue Cloud, Nue, or similar): product and pricing data models, quote and order lifecycle, approval automation, and amendments and renewals, including custom code written against the CPQ package rather than configuration alone\n Experience integrating Salesforce with billing, ERP, or provisioning systems via REST/Bulk APIs, middleware (Workato, Mulesoft, or similar), or direct callouts\n Fluency with SFDX, source-controlled metadata, and a sandbox-to-prod release process with peer review\n Active use of AI-assisted development tools (Claude, Copilot, Cursor, or similar) as part of how you write and review code, and the ability to speak to how you steer and verify their output\n Basic SQL skills and comfort working alongside a data warehouse\n Effective communication with sales, deal desk, finance and accounting, product, and engineering stakeholders\n \n Preferred qualifications \n \n Salesforce Platform Developer I and II certifications\n Advanced Administrator or Application/System Architect certification\n Deep understanding of Salesforce platform constraints: governor limits, bulkification, sharing and visibility, recursion control, and how they surface in CPQ-specific situations such as large quotes, calculation performance, and bulk amendments\n Experience implementing a CPQ solution end to end or re-platforming from one CPQ to another, not just maintaining an existing one\n Experience with billing and finance platforms such as Stripe, Metronome, or Oracle, and with usage-based or consumption pricing models\n Working understanding of how CPQ design decisions flow through to bookings, invoicing, and revenue recognition\n Proven experience scaling Salesforce in a high-growth GTM environment\n The annual compensation range for this role is listed below. \n For sales roles, the r","salary_min":270000,"salary_max":345000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","agents","alignment","payments","code-generation"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5413374008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T00:26:16Z","expires_at":"2026-10-10T13:30:41.415803Z","created_at":"2026-09-09T13:30:33.190442Z","updated_at":"2026-09-10T13:30:41.557052Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3098d7fe-9844-4077-87c6-d515093dabf4"},{"id":"6727027e-137f-4260-b9f7-16ec993f03f4","company_id":"a0000000-0000-0000-0000-000000000001","title":"Lead, Security Controls Assurance - SOX","slug":"lead-security-controls-assurance-sox-c594bbb9","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n Anthropic's Security Governance, Risk, and Compliance (GRC) team is the connective tissue that holds the company accountable to its security and control commitments. We translate regulatory, customer, and voluntary obligations into controls that teams act on, and give leadership a bird's-eye view of how well we're meeting them. We're building toward continuous assurance, to challenge and evidence the performance of controls continuously rather than through periodic audits.\n As Anthropic prepares for life as a public company, the Sarbanes-Oxley (SOX) control environment over our technology stack is one of the most consequential things this team owns. As part of Security GRC's technical controls assurance function, you will be the voice on what the IT general controls must achieve to support SOX 404 compliance. In partnership with Internal Audit, you will define control requirements and acceptance criteria for the in-scope engineering systems and infrastructure that underpin financial reporting. You will pair with engineering as they design and implement against those requirements, and validate that what ships actually meets the bar before Internal Audit and our external auditors test it. You are the product owner for control design methodology and continuous control monitoring, initially around ITGCs, but extending into other areas of security and compliance to drive visibility where and when we need it. \n Key responsibilities \n \n \n Define control requirements and acceptance criteria across the core ITGC domains of logical access, change management, computer operations, and program development for SOX in-scope systems, including home-built platforms where the control has to be designed into the system rather than bolted on.\n \n Set the bar for in-scope systems from day one. As financially significant systems are built, migrated, or replaced, define what the system must provide (auditability, segregation of duties, change control, immutable logging, evidence retention) before go-live, so controls are not retrofitted after the fact.\n \n Pressure-test changes for SOX impact during design. Review major infrastructure, system, and agent framework changes for control impact while decisions are still cheap, and maintain a clear view of which changes alter the SOX scope, key control population, or evidence requirements.\n \n Own second-line control monitoring and evidence readiness. Stand up continuous controls monitoring and automated evidence collection for ITGCs (control testing, walkthrough preparation, population and completeness validation, and mapping to the common controls framework). Materially raise automated evidence coverage and cut audit prep time.\n \n Drive control deficiency remediation with cross functional partners. Track and root-cause ITGC deficiencies surfaced by monitoring, Internal Audit, or external audit; partner with engineering owners on remediation design; and assess whether remediation actually closes the gap before re-testing.\n \n Assess scope changes through a SOX lens. When new products, entities, systems, or integrations come into scope, provide technical and compliance assessment of their impact on control design, evidence requirements, and engineering effort before commitments are made.\n \n Maintain alignment with the broader compliance portfolio. Where SOX ITGCs overlap with SOC 2, ISO 27001/42001, or other frameworks, ensure controls are designed once and evidenced once, and that changes made for one framework do not silently break another.\n \n Minimum qualifications \n \n \n Thrive at the pace of a hypergrowth company. You're comfortable making calls with incomplete information and reprioritizing as scope shifts.\n \n Have led or been a senior contributor to an ITGC program through SOX 404 readiness and/or at a public company, with a working command of PCAOB AS 2201, COSO 2013, and how external auditors scope, test, and evaluate technology controls and deficiencies.\n \n Have genuine engineering fluency, possibly from an earlier engineering career: you can read code and Terraform, follow a CI/CD pipeline end to end, and challenge a design on its technical merits.\n \n Have programming skills in Python or at least one systems language such as Go, Rust, or C/C++.\n \n Have deep familiarity with developer platform, release engineering, cloud infrastructure, or ERP/financial systems control domains.\n \n Understand the role of the second line: you can advise and challenge engineering without taking ownership of their controls, and you know where the line sits between your monitoring and Internal Audit's independent testing.\n \n Are a strong collaborat","salary_min":410000,"salary_max":510000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","alignment","agents","llm","payments"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5415864008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T23:45:03Z","expires_at":"2026-10-10T13:30:28.296091Z","created_at":"2026-09-09T13:30:22.77257Z","updated_at":"2026-09-10T13:30:28.432787Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6727027e-137f-4260-b9f7-16ec993f03f4"},{"id":"a81e1a5f-332d-4680-b515-0b98223be092","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior AI Product Engineer","slug":"senior-ai-product-engineer-frameworks-6423166b","description":"Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from.\n\nWhy Join the Drata Team? \nAt Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for:\n\n - Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go.\n\n - Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them.\n\n - A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level.\n\n - Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience.\n\n - A crew, not just coworkers: Dratanauts consistently describe a \"come as you are\" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here https://drata.com/about/careers/life and follow us on LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all for company news, employee stories, and career updates.\n\nJob Summary:\n\nDrata is reimagining compliance as an intelligent, always-on experience — and AI is at the center of that vision. We are seeking a Senior AI Product Engineer to own the full-stack development of customer-facing AI features, embedded directly within our product teams.\nThis is not a platform or infrastructure role. You'll translate the capabilities of LLMs, agents, and RAG pipelines into intuitive, polished product experiences — streaming chat interfaces, agentic workflows, intelligent summaries, and guided automation that makes compliance feel effortless. You'll partner closely with AI Engineers who own the backend intelligence and Product and Design who shape the vision, but you are the engineer who closes the loop between AI capability and the customer experience.\n\nWhat you'll do:\n\n - Build AI-powered product features end-to-end — React/TypeScript UI through Node.js/Python backend — with real-time streaming, graceful degradation, and human-in-the-loop interaction patterns\n\n - Translate AI capabilities — RAG pipelines, agentic workflows, structured reasoning — into interactions that feel natural to compliance practitioners\n\n - Partner with AI Engineers to define API contracts and output schemas; translate RAG pipelines, agentic workflows, and structured reasoning into interactions that feel natural to compliance practitioners\n\n - Advocate for the user's perspective in technical decisions; surface where model outputs break down in practice and iterate the product layer accordingly\n\n - Build user-facing feedback loops that capture signal on AI output quality and make it actionable for the broader AI team\n\n - Instrument AI features with product-level observability — latency, engagement, task completion, drop-off — alongside integration and end-to-end tests that validate behavior across the full stack\n\n - Establish reusable patterns (streaming hooks, feedback components, AI state management) that accelerate future AI feature development\n\n - Mentor engineers newer to AI product development; participate in design reviews with both engineering depth and product instinct\n\nWhat you'll bring:\n\n - Experience: 5+ years of software engineering experience with a proven track record of shipping full-stack features in production; 2+ years working on AI-powered product features\n\n - Frontend: Strong proficiency in React and TypeScript; experience building responsive, interactive UIs that handle async, streaming, and real-time data gracefully\n\n - Backend: Solid Python and Node.js and Typescript skills; experience designing and consuming APIs that integrate with LLM providers, orchestration frameworks, or AI services\n\n - AI Fluency: Hands-on experience building with LLM APIs (OpenAI, Anthropic, etc.); practical understanding of prompt engineering, context management, RAG, Quality/Evals(Braintrust or others) and structured outputs — not just calling an endpoint, but knowing what makes a prompt reliable in production\n\n - Familiarity with agent frameworks (LangGraph, LangChain, custom runtimes) and how to build product surfaces on top of multi-step agentic workflows\n\n - Streaming \u0026 Real-Time UI: Experience implementing streaming response patterns (SSE, WebSockets, chunked HTTP) and building UIs that handle p","salary_min":150000,"salary_max":230000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["healthcare","llm","rag","agents"],"apply_url":"https://jobs.ashbyhq.com/drata/16a05c2f-c8a2-47c5-995b-9a817a8955ba/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T23:30:09.318Z","expires_at":"2026-10-10T13:46:01.394135Z","created_at":"2026-06-28T14:13:54.057876Z","updated_at":"2026-09-10T13:46:01.527162Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a81e1a5f-332d-4680-b515-0b98223be092"},{"id":"9fcc630c-8790-4f48-86e3-a2f60a9e04fb","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Research Scientist, Map Scalability","slug":"research-scientist-map-scalability-1d31a031","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation. \n You will: \n \n Solve fundamental and applied research problems related to world understanding using VLMs, generative modeling and 3D reconstruction at large scale.\n Prototype and iterate on various research ideas using Waymo's internal driving data\n Scale and productionize world understanding solutions in collaboration with engineering teams across Waymo\n Present research findings to a wide audience within Waymo and Alphabet, with the possibility of publishing results to the research community\n \n You have: \n \n Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, or in a similar discipline.\n 1-3+ years of experience in a related field.\n Expert in either Foundational VLMs, Computer Vision or learning-based 3D reconstruction methods (3DGS, NeRF).\n Strong ML software engineering skills in Python/C++ with an ability to rapidly prototype solutions.\n Familiarity with major ML Frameworks (JAX, Tensorflow, Pytorch).\n \n We prefer: \n \n Publications at top-tier conferences like CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc.\n Hands-on experience productionizing and scaling ML solutions beyond the research stage.\n Fundamentals in 3D vision and/or computer graphics.\n Domain experience in the autonomous vehicle or simulation space.\n \n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $213,000 — $263,000 USD","salary_min":213000,"salary_max":263000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","tensorflow","computer-vision","autonomous-vehicles","pytorch","computer-graphics","reinforcement-learning","research"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8180692","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T21:50:14Z","expires_at":"2026-10-10T13:35:39.783392Z","created_at":"2026-09-09T13:35:07.865424Z","updated_at":"2026-09-10T13:35:39.919497Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9fcc630c-8790-4f48-86e3-a2f60a9e04fb"},{"id":"7fe686f5-09e9-4a22-9dd3-4581f7144b23","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Senior Director, Forward Deployed Engineering, Americas","slug":"senior-director-forward-deployed-engineering-americas-c16a8fef","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n C3 AI is seeking a Senior Director of Forward Deployed Engineering, Americas , based in Redwood City, California, to lead and scale our customer-facing engineering organization across the region.\n This role reports to the Vice President of Forward Deployed Engineering and will lead multiple Forward Deployed Engineering pods, with 5-10 FDE Managers and senior technical leaders reporting directly into the role and total organizational accountability for approximately 50-100 engineers across the Americas region.\n The Senior Director will be responsible for the performance, development, deployment, and technical quality of the Americas FDE organization. This leader will work closely with Industry Solution Leaders, Sales, Product, Platform, Engineering, and customer executives to ensure C3 AI teams are solving the right problems, delivering production-quality applications, and creating measurable customer value.\n The ideal candidate is a proven engineering leader who has built and managed highly technical organizations, remains credible and hands-on with software and architecture, and is equally comfortable reviewing code, coaching engineering managers, leading a customer escalation, or discussing delivery and organizational priorities with senior executives.\n Responsibilities \n \n Lead the Americas Forward Deployed Engineering organization. Manage, develop, and scale multiple FDE pods and their managers, with accountability for engineering performance, customer outcomes, talent development, and organizational health across the region.\n Own regional technical execution. Ensure Forward Deployed Engineering teams consistently design, build, deploy, and scale production-quality enterprise AI applications on the C3 AI Platform.\n Lead and develop engineering managers. Establish clear expectations for FDE Managers; coach them on technical leadership, people management, staffing, performance management, and customer execution; and build a strong pipeline of future engineering leaders.\n Set the operating model for the region. Define how FDE teams are organized, staffed, deployed, and managed across customer accounts, balancing customer priorities, technical fit, capacity, development opportunities, and business needs.\n Maintain accountability for customer delivery. Review engagement health, technical progress, risks, staffing, and delivery commitments across the Americas portfolio and intervene when projects require additional leadership or technical direction.\n Serve as the senior technical escalation point. Engage directly with strategic customers, senior engineers, architects, and executives on complex technical challenges, solution reviews, production readiness, and critical delivery situations.\n Establish and enforce engineering standards. Drive consistent standards for software architecture, application design, code quality, testing, security, scalability, maintainability, and production readiness across customer deployments.\n Stay technically engaged. Maintain sufficient hands-on technical depth to review architecture and code, challenge technical decisions, troubleshoot complex problems, and directly support critical customer engagements when needed.\n Build and retain a high-performing organization. Partner with Talent Acquisition and FDE leadership to recruit exceptional engineers and managers, maintain a high hiring bar, develop technical talent, manage performance, and create compelling career paths.\n Partner with Industry Solution Leaders. Ensure strong alignment between domain leadership and engineering execution, with clear accountability for translating customer problems and business objectives into technically sound, scalable solutions.\n Partner with Sales, Product, Platform, and Engineering leadership. Support strategic opportunities, account planning, solution design, product feedback, technical escalations, and prioritization across the Americas customer portfolio.\n Drive continuous improvement. Identify recurring technical and delivery patterns across customer engagements and translate field experience into improved engineering practices, reusable solution patterns, training, and product capabilities.\n Communicate with senior leadership. Provide clear, actionable visibility into organizational performance, customer delivery, staffing, technical risk, hiring, and areas requiring executive support.\n Travel to customer and C3 AI locations as required.\n \n Qualifications \n \n Bachelor's degree in ","salary_min":250000,"salary_max":350000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","cloud","agents","distributed-systems"],"apply_url":"https://c3.ai/job-description/8786629002?gh_jid=8786629002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T21:48:48Z","expires_at":"2026-10-10T13:41:21.459341Z","created_at":"2026-09-09T13:41:06.644923Z","updated_at":"2026-09-10T13:41:21.631723Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7fe686f5-09e9-4a22-9dd3-4581f7144b23"},{"id":"fcbda9e7-0967-415e-bb25-4c87e2b995b2","company_id":"82d2abc2-444c-4d89-9646-4739e72d700d","title":"Senior Engineering Manager, Machine Learning","slug":"senior-engineering-manager-machine-learning-813e6eec","description":"About Checkr Checkr is building the data platform to power safe and fair decisions. Over 140,000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job, a new place to live, a car ride, childcare, even a date. Customers include Uber, Pennymac, Airbnb, Doordash, and Anthropic. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company .\n We are hiring a Senior Engineering Manager to lead the Machine Learning Engineering team inside Checkr’s Data \u0026 ML organization. This team sits at the heart of our product's strategic advantage, making millions of background checks faster, more accurate, and more trustworthy.\n The team owns three connected areas:\n \n Core product intelligence: NLP and classification systems, entity resolution, profile integrity, model accuracy, and the production services that power Checkr’s products.\n Workforce integrity: resume and identity fraud, multi-signal risk detection, and new products that help customers identify sophisticated hiring fraud\n ML and agent infrastructure: evaluation systems, observability, model lifecycle, agent orchestration, and reusable infrastructure that helps every team ship reliable AI faster.\n \n This is an engineering leadership role, not a research-management role: you will lead ML engineers across seniority levels, stay close enough to the work to set technical direction, and hold the team accountable for production outcomes. You will decide where ML should continue to create a strategic advantage for Checkr.\n You will also shape Checkr’s broader AI strategy. The near-term agenda includes building a measurable accuracy moat in our core products, launching an end-to-end workforce-integrity product, and creating the evaluation and knowledge infrastructure required to operate AI agents in a regulated domain. This role reports to the Sr. Director of Data \u0026 ML within Engineering. This role is based in San Francisco. We are looking for someone who is seeking less process and more shipping, less paperwork and more results.\n What you’ll do \n \n Lead and grow the ML Engineering team . Hire, coach, and develop ML engineers. Set clear ownership, grow technical leaders, and build a team that generates its own roadmap.\n Set the strategy and roadmap . Turn ambiguous company priorities into a focused, multi-quarter ML agenda. Put investment on work that improves customer outcomes, revenue, accuracy, reliability, or cost. Stop work that does not.\n Raise the production engineering bar . Models and agents ship as dependable software: clear APIs, tests, CI/CD, observability, on-call ownership, and defined reliability targets.\n Build the ML operating model. Establish shared approaches to evaluation, golden sets, training-data provenance, model and prompt versioning, monitoring, retraining, latency, and cost. Replace artisanal evaluation with repeatable systems.\n Advance core product intelligence . Guide systems for classification, information extraction, entity resolution, profile integrity, and accuracy. Make model quality measurable in production and drive the feedback loops that improve it.\n Launch new AI and fraud products . Partner with Product, Security, Operations, and go-to-market teams to turn signals across identity, resume, device, and employment data into customer products.\n Lead Checkr’s agentic transition . Guide the design of AI systems that combine specialized models, LLMs, tools, and governed knowledge. \n Operate as an executive partner . Explain technical choices and risks in plain language. Align Product Engineering, Product, Operations, Legal, Security, and company leadership when incentives or constraints conflict.\n Model AI-native leadership . Use AI to increase the team’s speed and ambition. Keep ownership of every output. As generated code becomes cheaper, raise the bar on judgment, verification, and system design.\n \n What you bring \n \n 10+ years building software and machine learning or AI systems, with a clear progression in scope and impact.\n 3+ years managing ML or software engineers, including hiring and developing senior and staff-level technical leaders.\n A strong software-engineering foundation and a record of shipping ML systems that run in production.\n Technical depth across the ML lifecycle: data and labeling, experimentation, model selection, deployment, APIs, CI/CD, observability, evaluation, retraining, and incident response.\n Sound judgment across classical ML, deep learning, LLMs, rules, and conventional software.\n Experience setting direction for NLP, classification, extraction, entity resolution, risk, fraud, recommendation, or similarly complex applied-ML domains.\n Fluency with modern LLM systems, including structured outputs, tool use, agent orchestration, retrieval, evaluation, latency, quality, and cost trade-off","salary_min":268000,"salary_max":315000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","mlops","llm","deep-learning","nlp","healthcare","legal","payments"],"apply_url":"https://job-boards.greenhouse.io/checkr/jobs/8178764","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T20:16:47Z","expires_at":"2026-10-10T13:42:16.526296Z","created_at":"2026-09-09T13:41:56.337558Z","updated_at":"2026-09-10T13:42:16.725052Z","company_name":"Checkr","company_slug":"checkr","company_logo_url":"https://www.google.com/s2/favicons?domain=checkr.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fcbda9e7-0967-415e-bb25-4c87e2b995b2"},{"id":"4baa1de6-88bc-4d85-994e-a96b1b977082","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior Data Scientist, Risk and Support","slug":"senior-data-scientist-risk-and-support-a8b60936","description":"Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us.\n The Role \n The Data Science team at Block turns unique customer and product data into decisions that expand access to financial services. Our Support and Risk team powers decisioning behind Cash App, Afterpay, Square, and the next generation of Operations automation.\n We’re looking for a Data Scientist to help build, measure, and improve Risk and Support Operations that serve our customers with speed and quality. You’ll partner closely with product, engineering, and risk teams to define metrics, evaluate experiments, understand customer behavior, and turn ambiguous product questions into clear decisions.\n This is an agentic data science role. You’ll use AI tools and agent workflows to move faster and think more rigorously across the full data science loop: exploring messy datasets, building pipelines, stress-testing hypotheses, evaluating product changes, and turning analysis into decisions.\n You Will \n \n Turn complex product, customer, and risk data into clear insights, decision frameworks, and durable measurement systems for product, risk, and business partners\n Use AI tools and agent workflows to improve both the speed and quality of analytical work, from accelerating exploration and automating repetitive tasks to generating hypotheses and stress-testing conclusions\n Own end-to-end execution across analysis, metrics definition, experimentation, forecasting, visualization, and decision support\n Define and maintain measurement frameworks for Support and Risk Operations,  including contact demand forecasting, Staffing modeling, queue health and optimization.\n Partner with risk teams to evaluate model and policy performance, monitor cohorts, identify bias or drift, and connect risk decisions to product and business impact\n Design and analyze experiments, rollouts, and policy changes that shape customer access, repayment outcomes, and product growth\n Approach ambiguous Risk and Support questions from first principles, using statistical judgment to define the right cohorts, metrics, and decision criteria\n Communicate insights clearly to technical, product, and business stakeholders, including risk partners and senior decision-makers\n Lead technical direction and standards for the Block Data Science team - making and building consensus on key technical decisions, and creating reusable frameworks, measurement templates, and scalable tooling that remove complexity for others.\n Drive localized cross-team impact by connecting measurement and insights across Support and Risk Operations and partnering with senior stakeholders in product, engineering, and risk to align Data Science work with broader strategy.\n Mentor and grow the team by developing junior data scientists, fostering a culture of analytical rigor and psychological safety, and contributing to hiring through interviews and calibrations\n \n You Have \n \n A bachelor’s degree in statistics, data science, economics, computer science, or a similar quantitative field with 12+ years of experience in a relevant role OR\n A graduate degree in statistics, data science, economics, computer science, or a similar quantitative field with 6-8+ years of experience in a relevant role\n Advanced proficiency with SQL and experience building clear, decision-oriented data visualizations\n Strong product, analytical, and statistical judgment, including the ability to turn ambiguous product, customer, or risk questions into sound analyses, communicate tradeoffs clearly, and support decisions\n Experience using AI tools to improve the speed, quality, and durability of analytical work \n \n  \n We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who ","salary_min":168300,"salary_max":252500,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","fine-tuning","cloud","payments","data-science"],"apply_url":"http://block.xyz/careers/jobs/5418716008?gh_jid=5418716008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T19:56:46Z","expires_at":"2026-10-10T13:40:54.942261Z","created_at":"2026-09-09T13:40:41.18641Z","updated_at":"2026-09-10T13:40:55.065974Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4baa1de6-88bc-4d85-994e-a96b1b977082"},{"id":"3e0e7cd5-b563-4c98-bea8-e648a92390b9","company_id":"92df3417-f362-4f1a-9406-e34d8013b283","title":"Senior Data Scientist, Risk and Support","slug":"senior-data-scientist-risk-and-support-1f2d003b","description":"Block builds simple, powerful tools that make progress towards an economy that’s truly open to all. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone. Join us.\n The Role \n The Data Science team at Block turns unique customer and product data into decisions that expand access to financial services. Our Support and Risk team powers decisioning behind Cash App, Afterpay, Square, and the next generation of Operations automation.\n We’re looking for a Data Scientist to help build, measure, and improve Risk and Support Operations that serve our customers with speed and quality. You’ll partner closely with product, engineering, and risk teams to define metrics, evaluate experiments, understand customer behavior, and turn ambiguous product questions into clear decisions.\n This is an agentic data science role. You’ll use AI tools and agent workflows to move faster and think more rigorously across the full data science loop: exploring messy datasets, building pipelines, stress-testing hypotheses, evaluating product changes, and turning analysis into decisions.\n You Will \n \n Turn complex product, customer, and risk data into clear insights, decision frameworks, and durable measurement systems for product, risk, and business partners\n Use AI tools and agent workflows to improve both the speed and quality of analytical work, from accelerating exploration and automating repetitive tasks to generating hypotheses and stress-testing conclusions\n Own end-to-end execution across analysis, metrics definition, experimentation, forecasting, visualization, and decision support\n Define and maintain measurement frameworks for Support and Risk Operations,  including contact demand forecasting, Staffing modeling, queue health and optimization.\n Partner with risk teams to evaluate model and policy performance, monitor cohorts, identify bias or drift, and connect risk decisions to product and business impact\n Design and analyze experiments, rollouts, and policy changes that shape customer access, repayment outcomes, and product growth\n Approach ambiguous Risk and Support questions from first principles, using statistical judgment to define the right cohorts, metrics, and decision criteria\n Communicate insights clearly to technical, product, and business stakeholders, including risk partners and senior decision-makers\n Lead technical direction and standards for the Block Data Science team - making and building consensus on key technical decisions, and creating reusable frameworks, measurement templates, and scalable tooling that remove complexity for others.\n Drive localized cross-team impact by connecting measurement and insights across Support and Risk Operations and partnering with senior stakeholders in product, engineering, and risk to align Data Science work with broader strategy.\n Mentor and grow the team by developing junior data scientists, fostering a culture of analytical rigor and psychological safety, and contributing to hiring through interviews and calibrations\n \n You Have \n \n A bachelor’s degree in statistics, data science, economics, computer science, or a similar quantitative field with 12+ years of experience in a relevant role OR\n A graduate degree in statistics, data science, economics, computer science, or a similar quantitative field with 6-8+ years of experience in a relevant role\n Advanced proficiency with SQL and experience building clear, decision-oriented data visualizations\n Strong product, analytical, and statistical judgment, including the ability to turn ambiguous product, customer, or risk questions into sound analyses, communicate tradeoffs clearly, and support decisions\n Experience using AI tools to improve the speed, quality, and durability of analytical work \n \n  \n We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who ","salary_min":168300,"salary_max":252500,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["payments","fine-tuning","cloud","agents","data-science"],"apply_url":"http://block.xyz/careers/jobs/5412922008?gh_jid=5412922008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T19:55:55Z","expires_at":"2026-10-10T13:40:55.018575Z","created_at":"2026-09-09T13:40:41.525704Z","updated_at":"2026-09-10T13:40:55.14487Z","company_name":"Block","company_slug":"block","company_logo_url":"https://www.google.com/s2/favicons?domain=block.xyz\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3e0e7cd5-b563-4c98-bea8-e648a92390b9"},{"id":"53da8665-dbaa-4963-8789-47e18de045e6","company_id":"52f44519-9f93-4eac-ae0b-8be13e385ebe","title":"Legal Operations Manager","slug":"legal-operations-manager-98cdf330","description":"LEGAL OPERATIONS MANAGER\n\n\n\nYou'll be the operational engine behind how Firecrawl's legal function actually runs. Reporting to the General Counsel, this is a build-from-scratch role: as we scale, someone has to stand up the systems, processes, and vendor relationships that let a lean legal team keep pace with a company growing this fast. That's you.\n\nThis is not primarily an administrative job. It's an operational build role for someone who is genuinely energized by designing systems from nothing, who can pick up a messy process and turn it into something repeatable that engineers, salespeople, and executives actually use. You'll work across commercial contracting, compliance, legal technology, product, and regulatory matters, not by practicing law, but by building the machinery that lets the lawyers move fast.\n\nWe care more about judgment, ability, and initiative than about the path you took to get here.\n\n \n\nSalary Range: $140,000–$160,000/year (Range shown is for U.S.-based employees in San Francisco, CA. Compensation is adjusted fairly based on your location's cost of living.)\n\nEquity Range: Competitive equity - details shared during the process. \n\nLocation: San Francisco, CA (Preferred); Open to Remote (US, UTC-5 to UTC-10)\n\nJob Type: Full-Time\n\nExperience: Has demonstrated high achievement, is highly organized, and high agency. Background is flexible, see below*.\n\nVisa: Must be legally authorized to work in the United States. We're not able to sponsor visas right now, though that may change down the line.\n\n\n\n\nABOUT FIRECRAWL\n\nFirecrawl is the easiest way to turn the web into data AI agents can use. One API call converts any URL into clean, LLM-ready markdown or structured data - the boring-hard problem everyone building with LLMs eventually hits, solved.\n\nWe hit 8 figures in ARR in year one and more than doubled it in year two. We have 175k+ GitHub stars, and developers, agents, and category-defining AI companies build on us every day. Growth like this is rare, and we're just getting started.\n\nWe're a small team punching far above our weight. Everyone here owns a real piece of the product and company, end to end, and runs it themselves - no hiding behind process or headcount.\n\nThis is a place for people who want to work at the frontier: an AI company building the infrastructure other AI companies run on, not one bolting AI onto an existing product. We move fast, go deep, and are building the tools superintelligence will rely on to gather data from the web.\n\n\n\n\nWHAT YOU'LL DO\n\n - Build and maintain the contract management, legal operations, and compliance systems the function runs on\n\n - Own the legal technology stack: CLM, e-billing, matter management. Pick the tools, run them, make them work\n\n - Build and run contract intake and routing, from first request to signature\n\n - Take on the creative and novel tasks that don't require a law degree but do require someone reliable to own them end to end\n\n - Support the legal team on research, regulatory monitoring, and special projects\n\n - Work with finance, sales, product, engineering, HR, and security to keep legal workflows moving\n\n - Manage outside counsel and legal vendor relationships, including billing, budgets, and engagement terms\n\n - Find the repetitive work and standardize, automate, or kill it with technology and AI\n\n - Track legal spend, contract volume, and turnaround time, and report out on where things actually stand\n\n - Take on more ownership over time, shaped by what you're good at and what you want to get good at\n   \n   \n\n\nWHAT WE'RE LOOKING FOR\n\nStrong candidates may come from legal operations, contracts, compliance, business operations, consulting, technology, professional services, or somewhere else entirely. What matters is that the work was complex and you were the one who owned the details.\n\n - You process a lot of AI output without shipping slop. You can run large volumes of AI-generated content through your own judgment and have what comes out the other side be right. This is the single most important thing on this list\n\n - You drive projects to done independently. Nobody is going to hand you a plan or check your work at every step\n\n - You've built or meaningfully improved a process, not just maintained one that was already there\n\n - You turn a vague ask into a working process. Undefined scope is the fun part, not the blocker\n\n - You're extraordinarily organized and you close loops without being chased\n\n - You're excellent in writing and out loud, with sales, finance, and leadership, not just with lawyers\n\n - You have good judgment and real discretion with confidential information\n\n - You master new tools fast. Every system here will be new to you and that shouldn't slow you down\n\n - You're intellectually curious about how legal, business, and technology decisions actually get made\n\n - You're an AI super user. Hard requirement, not a nice-to-have. You reach for AI to move faster by default\n\nA law degree is not required, and this r","salary_min":140000,"salary_max":160000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["llm","payments","agents","legal"],"apply_url":"https://jobs.ashbyhq.com/firecrawl/b1db13d1-402c-40e9-95fa-4ac67bacb078/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-08T18:12:40.049Z","expires_at":"2026-10-10T13:47:12.546043Z","created_at":"2026-09-08T13:46:21.349109Z","updated_at":"2026-09-10T13:47:12.671676Z","company_name":"Firecrawl","company_slug":"firecrawl","company_logo_url":"https://www.google.com/s2/favicons?domain=firecrawl.dev\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/53da8665-dbaa-4963-8789-47e18de045e6"}],"page":1,"per_page":20,"total":9143,"total_is_exact":true,"total_pages":458}