{"has_next":true,"jobs":[{"id":"aae8b669-3776-4de3-8b0f-32302056ea43","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Data Infrastructure","slug":"senior-software-engineer-data-infrastructure-4c459d4c","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\nWe organize around four focus areas:\n\n - Core Infra: The foundational cloud stack—networking, compute, storage, security, and infrastructure‑as‑code—to ensure reliability, scale, and cost efficiency.\n\n - Data Infra: Streaming/batch data platforms powering analytics/BI and customer‑facing telemetry, including for customer‑managed and on‑prem environments.\n\n - ML Infra: GPU and model‑serving platforms for LLM inference with multi‑provider routing and support for on‑prem/air‑gapped deployments.\n\n - Platform (DevEx): CI/CD, paved paths, and core services that make shipping fast, safe, and consistent across teams.\n\nOur mission is to deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately.\n\n \n\nAbout the Role\nWe're hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You'll own critical data pipelines and storage layers end‑to‑end, improve reliability and performance, and create paved paths that let every Decagon engineer work confidently with data at scale.\n\nIn this role, you will\n\n - Design and implement high‑throughput data pipelines and streaming systems with strong SLOs, clear runbooks, and actionable telemetry.\n\n - Build and operate real‑time and batch ingestion infrastructure using tools like Kafka, Flink, and Airflow.\n\n - Own our analytical data layer — schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar.\n\n - Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.\n\n - Tune pipeline and query latencies: optimize data paths, apply smart caching/partitioning, and hit tight p95/p99 targets.\n\n - Lead infrastructure‑as‑code (Terraform) and GitOps practices for data systems; reduce drift with reusable modules and policy‑as‑code.\n\n - Participate in on‑call and drive down toil through automation and elimination of recurring data issues.\n\nYour background looks something like this\n\n - 5+ years building and operating production data infrastructure at scale.\n\n - Hands-on experience with Tier 1 data technologies: ClickHouse, Kafka (or MSK/Pub‑Sub/RabbitMQ), and Flink or dbt.\n\n - Proven track record meeting high availability and low latency targets across streaming and batch workloads.\n\n - Excellent observability chops (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.\n\n - Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs.\n\nEven better if you have\n\n - Experience with CDC tooling (Debezium) and orchestration frameworks (Airflow, Dagster, or Prefect)\n\n - Familiarity with Spark or Dask for large‑scale data processing\n\n - Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks)\n\n - Experience being an early data/platform/infrastructure engineer at another company\n\n - Strong Kubernetes experience (GKE/EKS/AKS) and multi‑cloud exposure (GCP, AWS, Azure)\n\n - Experience with customer‑managed deployments\n\n \n\n\nCOMPENSATION\n\n$200K – $400K + Offers Equity\n\nThis range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.\n\nIn addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Take what you need vacation policy (","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","llm","data-pipeline","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/decagon/0d0beb6b-61a2-40e3-9955-adcff9cbc92e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T23:17:54.192Z","expires_at":"2026-06-29T14:07:13.674618Z","created_at":"2026-05-30T14:07:13.790812Z","updated_at":"2026-05-30T14:07:13.790812Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/aae8b669-3776-4de3-8b0f-32302056ea43"},{"id":"3b0f1d10-c226-4905-9392-d5d4cdceab10","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Data Infrastructure","slug":"senior-software-engineer-data-infrastructure-20b94406","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\nWe organize around four focus areas:\n\n - Core Infra: The foundational cloud stack—networking, compute, storage, security, and infrastructure‑as‑code—to ensure reliability, scale, and cost efficiency.\n\n - Data Infra: Streaming/batch data platforms powering analytics/BI and customer‑facing telemetry, including for customer‑managed and on‑prem environments.\n\n - ML Infra: GPU and model‑serving platforms for LLM inference with multi‑provider routing and support for on‑prem/air‑gapped deployments.\n\n - Platform (DevEx): CI/CD, paved paths, and core services that make shipping fast, safe, and consistent across teams.\n\nOur mission is to deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately.\n\n\n\nAbout the Role\nWe're hiring a Senior Data Infrastructure Engineer to design, build, and operate the data systems that power Decagon's AI products. You'll own critical data pipelines and storage layers end‑to‑end, improve reliability and performance, and create paved paths that let every Decagon engineer work confidently with data at scale.\n\nIn this role, you will\n\n - Design and implement high‑throughput data pipelines and streaming systems with strong SLOs, clear runbooks, and actionable telemetry.\n\n - Build and operate real‑time and batch ingestion infrastructure using tools like Kafka, Flink, and Airflow.\n\n - Own our analytical data layer — schema design, query performance, and cost optimization across ClickHouse, BigQuery, or similar.\n\n - Partner with research and product teams to architect data solutions, evaluate performance, and scale new features.\n\n - Tune pipeline and query latencies: optimize data paths, apply smart caching/partitioning, and hit tight p95/p99 targets.\n\n - Lead infrastructure‑as‑code (Terraform) and GitOps practices for data systems; reduce drift with reusable modules and policy‑as‑code.\n\n - Participate in on‑call and drive down toil through automation and elimination of recurring data issues.\n\nYour background looks something like this\n\n - 5+ years building and operating production data infrastructure at scale.\n\n - Hands-on experience with Tier 1 data technologies: ClickHouse, Kafka (or MSK/Pub‑Sub/RabbitMQ), and Flink or dbt.\n\n - Proven track record meeting high availability and low latency targets across streaming and batch workloads.\n\n - Excellent observability chops (OpenTelemetry, Prometheus/Grafana, Datadog) and strong incident response discipline.\n\n - Clear written communication and the ability to turn ambiguous data requirements into simple, reliable designs.\n\nEven better if you have\n\n - Experience with CDC tooling (Debezium) and orchestration frameworks (Airflow, Dagster, or Prefect)\n\n - Familiarity with Spark or Dask for large‑scale data processing\n\n - Experience with cloud data warehouses (Snowflake, BigQuery, Redshift, Databricks)\n\n - Experience being an early data/platform/infrastructure engineer at another company\n\n - Strong Kubernetes experience (GKE/EKS/AKS) and multi‑cloud exposure (GCP, AWS, Azure)\n\n - Experience with customer‑managed deployments\n\n\n\n\nCOMPENSATION\n\n$200K – $400K + Offers Equity\n\nThis range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.\n\nIn addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Take what you need vacation policy (subj","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","data-pipeline","agents","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/decagon/d400020b-2f97-4316-a8c2-9dc70f254cdd/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T23:14:29.883Z","expires_at":"2026-06-29T14:07:13.754967Z","created_at":"2026-05-30T14:07:13.876706Z","updated_at":"2026-05-30T14:07:13.876706Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3b0f1d10-c226-4905-9392-d5d4cdceab10"},{"id":"09d0acb5-52de-4a76-88c6-0eb844785025","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Research Scientist - RL Training","slug":"research-scientist-rl-training-ffdbae39","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n ABOUT THE ROLE  \n We're looking for a Research Scientist to work on reinforcement learning for training and aligning large language models. This is a foundational research role focused on one of the most consequential open data problems in AI: how to generate the data, reward signals, and training procedures that steer LLM behavior in reliable and generalizable directions — and a core capability that directly differentiates Snorkel's data-as-a-service offering. \n You'll work closely with Snorkel's research, engineering, and delivery teams to advance our RL data capabilities — translating research ideas into the preference datasets, reward models, and RL-ready corpora we produce for frontier AI labs, and contributing to a research agenda that is central to Snorkel's long-term differentiation as a provider of bespoke training data. \n MAIN RESPONSIBILITIES  \n \n Research and implement reinforcement learning techniques — including GRPO, RLHF, RLAIF, DPO, and reward modeling — and translate them into data products (preference datasets, reward signals, verifiable rewards) that customers can use to train and fine-tune large language models. \n Design and build data pipelines that generate high-quality training signal for RL workflows, including AI-assisted data annotation and curation data pipelines to improve model generalization to unseen benchmarks . \n Prototype and iterate on end-to-end RL training recipes that inform what data Snorkel ships as part of its data-as-a-service deliveries. \n Work closely with research scientists, ML engineers, and delivery teams to translate RL research into customer-ready data products.\n Stay current with the latest developments in large-scale muli-node LLM training, alignment research, and scalable RL methods (on complex environments such as Terminal-Bench), bringing relevant advances into Snorkel's data-as-a-service approach.\n Contribute to Snorkel's research publications and internal knowledge base in RL and model training.\n \n PREFERRED QUALIFICATIONS  \n \n Deep expertise in reinforcement learning from human or AI feedback, reward modeling and credit attribution ideally with a clear perspective on what data makes these techniques work. \n Experience training or fine-tuning 30B+ large language models at scale, including familiarity with distributed training infrastructure. \n Strong proficiency in Python and ML frameworks, especially PyTorch and HuggingFace and hands-on experience with RL frameworks such as Verl and SkyRL. \n Solid software engineering fundamentals — you can build research prototypes that others can run, extend, and integrate into data production workflows. \n Familiarity with ML infrastructure and cloud platforms and tools (AWS, GCP, Kubernetes, Slurm, etc.); experience with large-scale RL training pipelines a strong plus. \n Comfort operating in a high-iteration environment with open-ended research questions and shifting, customer-driven technical constraints. \n Ph.D. in machine learning, reinforcement learning, or a related field strongly preferred; exceptional industry experience considered. \n Salary Range \n $200,000 — $325,000 USD \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and haras","salary_min":200000,"salary_max":325000,"location":"Redwood City, CA","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["alignment","distributed-systems","pytorch","fine-tuning","generative-ai","data-pipeline","llm","reinforcement-learning"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6009496004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T21:22:40Z","expires_at":"2026-06-29T14:03:05.747327Z","created_at":"2026-05-30T14:03:05.857458Z","updated_at":"2026-05-30T14:03:05.857458Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/09d0acb5-52de-4a76-88c6-0eb844785025"},{"id":"8b3dbb78-3093-481e-9b0c-09e3ed1deb6e","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Principal Software Engineer, Data","slug":"principal-software-engineer-data-0cdb1bea","description":"Your Impact at LILA \n Join us in shaping the future of science! We are seeking Principal Software Engineers with backend experience to join our Data Platform Team (Data), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!\n About The Team \n The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.\n What You'll Be Building \n \n Design \u0026 Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in scalable backend system design.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening and writing skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to design complex backend solutions, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware\n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.\n Expected Base Salary Range\n $204,000 — $348,000 USD \n About LILA \n Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.\n LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials","salary_min":204000,"salary_max":348000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["cloud","pytorch","embeddings","robotics","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4250071009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T19:39:54Z","expires_at":"2026-06-29T14:17:40.451966Z","created_at":"2026-05-30T14:17:40.562155Z","updated_at":"2026-05-30T14:17:40.562155Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8b3dbb78-3093-481e-9b0c-09e3ed1deb6e"},{"id":"a6cf2026-eaea-495b-8177-860a11bedb45","company_id":"168d43fe-0922-420c-9743-59e0a899fd9d","title":"Data Scientist","slug":"data-scientist-24024c78","description":"A Career with Point72’s Technology Team\n As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications.\n As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business.\n  \n What you’ll do\n \n Lead the development and deployment of advanced models and algorithms that turn complex data into actionable insights to influence decisions across the organization\n Build and champion the rollout of a technology insights product, setting clear service standards, aligning stakeholders, and establishing transparent metrics to measure impact and drive adoption\n Design and maintain a centralized analytics platform that unifies key performance indicators, satisfaction scores, and operational metrics into intuitive dashboards for leadership\n Develop automated data pipelines and validation processes to gather, clean, and prepare large sets of structured and unstructured data for modeling and analysis\n Partner with data engineers, analysts, and business partners to translate business challenges into scalable, production-ready data solutions and shared standards\n Create reports and drill-down analyses that highlight service health, enable targeted action planning, and support proactive management\n Monitor and analyze performance across service quality, project manager satisfaction, efficiency, operational risk, and cost, highlighting trade-offs and providing strategic recommendations\n Use historical trend analysis and experimentation to uncover recurring issues, measure the impact of corrective actions, and drive continuous improvement\n Integrate third-party data sources and application programming interfaces into the analytics ecosystem to expand capabilities and enrich models\n Explore and implement modern cloud-native and distributed computing tools and methodologies to improve scalability, reliability, and reproducibility\n \n  \n What’s required\n \n 5–10 years of professional experience in data science or a closely related field in financial services or technology environments\n Bachelor's or master's degree in computer science, data science, statistics, engineering, or a related technical discipline\n Deep expertise in statistical modeling, machine learning, and data mining using Python, R, or similar programming languages\n Demonstrable experience with cloud-based analytics platforms, such as Amazon Web Services (AWS), and distributed computing frameworks, such as Spark or Databricks\n Strong skills in data wrangling, feature engineering, data quality management, and production data pipeline design\n Experience designing and implementing performance management systems, dashboards, or service excellence frameworks that inform leadership decisions\n Solid understanding of data architecture, data governance, reproducible research practices, and model monitoring in production\n Experience with version control systems—such as Git—continuous integration and delivery workflows, and modern workflow orchestration tools\n Proven ability to communicate complex analyses clearly to technical and non-technical stakeholders and to collaborate effectively in fast-paced, high-stakes environments\n Commitment to the highest ethical standards\n \n  \n We take care of our people\n We invest in our people, their careers, their health, and their well-being. When you work here, we provide:\n \n Fully-paid health care benefits\n Generous parental and family leave policies\n Volunteer opportunities\n Support for employee-led affinity groups representing women, people of color and the LGBT+ community\n Mental and physical wellness programs\n Tuition assistance\n A 401(k) savings program with an employer match and more\n \n  \n About Point72\n Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit  https://point72.com","salary_min":200000,"salary_max":300000,"location":"New York, NY","workplace":"onsite","job_type":"full-time","experience_level":"principal","tags":["distributed-systems","data-pipeline","mlops","data-science"],"apply_url":"https://boards.greenhouse.io/point72/jobs/8568268002?gh_jid=8568268002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T16:17:45Z","expires_at":"2026-06-29T14:11:58.685291Z","created_at":"2026-05-30T14:11:58.799327Z","updated_at":"2026-05-30T14:11:58.799327Z","company_name":"Point72","company_slug":"point72","company_logo_url":"https://www.google.com/s2/favicons?domain=point72.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a6cf2026-eaea-495b-8177-860a11bedb45"},{"id":"0d7d0e83-e4e7-436c-8ea8-9998eef08a01","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Android","slug":"helix-ai-engineer-android-4b9829bf","description":"Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose and require 5 days/week in-office collaboration. It’s time to build.\n We're looking for a Senior Android Engineer with deep expertise in low-level Android systems, the NDK, and real-time sensor and video pipelines. This is not a standard Android app role — you'll be building the mobile application that interfaces directly with our custom sensor hardware over USB, ingests high-frequency camera and IMU data in real time, and runs on-device AI inference at the edge.\n If you've spent time below the Java/Kotlin layer — writing C/C++ via the NDK, implementing custom HALs, or building zero-copy sensor pipelines — this role was built for you.\n WHAT YOU'LL DO \n \n Build and own the Android application that serves as the primary mobile interface to Figure's humanoid robots, connected via USB Host / Android Open Accessory protocols.\n Architect high-throughput, zero-drop data ingestion pipelines for high-FPS image sensors and high-frequency IMU data, using zero-copy memory techniques and real-time concurrency models.\n Implement custom hardware abstraction layers (HAL) and leverage the Android NDK (C/C++) for high-performance, low-latency processing.\n Optimize CPU/GPU workloads for real-time edge filtering under strict thermal and battery constraints, using foreground services and WorkManager for bulletproof background operation.\n Integrate on-device AI inference libraries (TFLite, MediaPipe, ONNX Runtime, OpenCV) for real-time computer vision and sensor fusion.\n Implement low-latency video streaming protocols (e.g. WebRTC) \n \n WHAT WE'RE LOOKING FOR \n \n Deep expertise in Android NDK (C/C++) — custom HAL development, USB Host/AOA protocol communication, and direct hardware interfacing below the standard SDK layer.\n Proven experience architecting real-time, low-latency data pipelines for high-bandwidth sensors — zero-copy memory, real-time concurrency, and synchronization with zero frame drops.\n Mastery of Android system resource management: CPU/GPU workload optimization, thermal and battery constraints, foreground services, and WorkManager.\n Strong proficiency in both C/C++ (NDK) and Kotlin/Java for Android.\n Experience shipping production Android applications in hardware-connected, latency-critical environments.\n Proven track record shipping and maintaining production Android applications at scale — including crash rate management, OTA update rollout strategies, real-time telemetry and monitoring pipelines, and sustaining reliability across a large, diverse active user base spanning multiple device configurations and Android OS versions\n \n NICE TO HAVE \n \n Experience integrating on-device CV/ML inference: TensorFlow Lite, MediaPipe, ONNX Runtime, or OpenCV applied to raw sensor feeds.\n Familiarity with WebRTC or other low-latency streaming protocols for real-time video.\n Background in DSP techniques applied directly to raw sensor data.\n Prior work in robotics companion apps, industrial Android devices, AR/computer vision mobile apps, automotive HMI, or drone control applications.\n \n The US base salary range for this full-time position is between $150,000 - $400,000 annually.\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":150000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","robotics","tensorflow","computer-vision","mobile"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4685209006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T22:27:59Z","expires_at":"2026-06-29T14:05:53.434799Z","created_at":"2026-05-29T14:18:08.419145Z","updated_at":"2026-05-30T14:05:53.546009Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0d7d0e83-e4e7-436c-8ea8-9998eef08a01"},{"id":"a944334e-23f0-4033-b1c8-307c9e7c7124","company_id":"75dcf7c0-5121-45f1-8d1b-6bfbfe15072f","title":"Helix AI Engineer, Backend Infrastructure ","slug":"helix-ai-engineer-backend-infrastructure-13269072","description":"Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose and require 5 days/week in-office collaboration. It’s time to build.\n We're looking for a senior-level backend engineer who has scaled high-throughput, low-latency data systems and has strong instincts around cloud infrastructure and real-time streaming pipelines. You'll architect and build the core backend systems that power Figure's real-time data infrastructure — enabling the scale and reliability that our AI and robotics platforms depend on.\n This is a high-ownership role at the intersection of media and sensor data streaming, cloud systems, and applied ML serving. You'll work closely with our AI and robotics teams to ensure latency, reliability, and throughput meet the demands of real-world robot operation.\n WHAT YOU'LL DO \n \n Architect and scale cloud backend infrastructure for high-concurrency, real-time streaming of media and sensor data across robot fleets and user sessions.\n Design and build low-latency data pipelines that ingest, route, and process high-bandwidth streams — including camera feeds, IMU data, and other robot sensor outputs — into our AI stack in real time.\n Own reliability, latency, and throughput SLAs for streaming and data infrastructure.\n Collaborate with AI and robotics teams to integrate ML model serving into real-time data pipelines.\n Build observability, alerting, and tooling to give the team full situational awareness over live robot traffic.\n Drive architectural decisions and mentor engineers across the team.\n \n WHAT WE'RE LOOKING FOR \n \n Deep experience scaling cloud backend systems handling high-concurrency, real-time data streams — media, sensor, telemetry, or equivalent high-bandwidth pipelines.\n Strong fundamentals in distributed systems: stream processing, connection management, data transport, and low-latency architecture.\n Proficiency in one or more backend languages (Go, C++, Python, Rust) and cloud platforms (AWS, GCP, or Azure).\n Experience with containerized infrastructure, service mesh, and large-scale deployment pipelines.\n Strong communication and cross-functional collaboration skills.\n \n NICE TO HAVE \n \n Hands-on experience integrating AI inference serving (Triton Inference Server, TensorRT, SageMaker, or similar) into real-time data pipelines.\n Background in robotics, autonomous vehicles, live media platforms, or other latency-critical streaming domains.\n Familiarity with protocols such as WebRTC, RTSP, gRPC, or Kafka for real-time data transport.\n Experience with on-device or edge inference and the tradeoffs of cloud vs. edge processing.\n \n The US base salary range for this full-time position is between $150,000 - $400,000 annually.\n The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.","salary_min":150000,"salary_max":400000,"location":"San Jose, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["robotics","mlops","api-design","autonomous-vehicles","cloud","gpu","data-pipeline","distributed-systems"],"apply_url":"https://job-boards.greenhouse.io/figureai/jobs/4685172006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T21:42:25Z","expires_at":"2026-06-29T14:05:53.514412Z","created_at":"2026-05-29T14:18:08.491663Z","updated_at":"2026-05-30T14:05:53.629497Z","company_name":"Figure AI","company_slug":"figure-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=figure.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a944334e-23f0-4033-b1c8-307c9e7c7124"},{"id":"64170ac3-3bc0-4e64-aa55-14d395814525","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Machine Learning Engineer II, Ads Response Prediction","slug":"senior-machine-learning-engineer-ii-ads-response-prediction-c8a2de33","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language models.\n The Ads Response Prediction team owns all systems, algorithms and ML models to ensure a relevant and engaging Ads experience to customers of all the platforms powered by Instacart. This includes search and exploration retrieval systems, sequential modeling and generative retrieval systems for next interaction recommendations, LLM integrations, relevance models, pCTR models, bidding models and incrementality models. The team optimizes for an efficient marketplace to ensure delightful customer shopping experience, desirable advertiser business outcome and Instacart Ads revenue.\n The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines, Ray-based distributed training, and automated model deployment. This means you can focus your energy on advancing modeling science rather than building infrastructure.\n About the Job \n \n Lead research and development of pCTR and conversion prediction models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer’s curse), and advancing model accuracy across Instacart’s ads surfaces.\n Design and implement debiasing techniques such as Mixed Negative Sampling (MNS), Inverse Propensity Weighting (IPW), counterfactual risk minimization, and calibration methods (Platt scaling, isotonic regression) to address systematic prediction biases.\n Contribute to the next-generation Multi-Domain Multi-Task (MDMT) model architecture, incorporating innovations like Mixture-of-Experts (MoE), Transformer layers for sequential user behavior, and LoRA adaptors for scalable domain fine-tuning.\n Drive sequence modeling initiatives including the TIGER generative retrieval system and Semantic ID representation learning, expanding their application across ads surfaces such as Product Details, Search and other placements.\n Collaborate with the broader ML community in the company on the path toward Foundation Models using autoregressive user behavior prediction.\n Formulate and scope ambiguous modeling problems from first principles. Translate business observations (e.g., overcalibration patterns, cold-start underperformance) into well-defined ML research directions with clear evaluation criteria.\n Publish and present findings internally. Contribute to the team’s culture of technical rigor through design reviews, paper sharing, and experiment retrospectives.\n \n About You \n Minimum Qualifications \n \n PhD/Master in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field.\n 6+ years of combined academic and industry experience (including PhD research) applying ML to ranking, recommendation, or prediction problems at scale.\n Deep understanding of CTR/conversion prediction modeling, including familiarity with architectures such as Deep \u0026 Wide, DeepFM, DCN, and multi-task learning formulations.\n Strong foundation in causal inference, counterfactual reasoning, and","salary_min":201000,"salary_max":212000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["llm","pytorch","deep-learning","generative-ai","data-pipeline","mlops","fine-tuning","distributed-systems"],"apply_url":"https://instacart.careers/job/?gh_jid=7963838","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T19:10:27Z","expires_at":"2026-06-29T14:08:41.426586Z","created_at":"2026-05-29T14:32:35.186075Z","updated_at":"2026-05-30T14:08:41.541147Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/64170ac3-3bc0-4e64-aa55-14d395814525"},{"id":"06abea54-0601-42e3-bb89-32ddb1ee619d","company_id":"3029e985-56bf-4ac2-9ae1-df4cdd53b12f","title":"Sr. Staff Software Development Engineer-AI Security","slug":"sr-staff-software-development-engineer-ai-security-6fd417d1","description":"About Zscaler \n Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.\n Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability.\n We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.\n Role \n We are looking for a Sr. Staff Software Development Engineer-AI Security to join us as a founding member of our AI Security Team. This is a Hybrid role based in San Jose, CA or Bellevue, WA (3 days in office), reporting to the Director of Software Engineering within the Emerging Tech org.\n You will be responsible for designing and implementing core infrastructure components and distributed systems, serving as a foundational architect for our AI security solution. This high-impact role focuses on scaling security infrastructure to support hundreds of millions of users, collaborating with stakeholders across the development lifecycle to drive innovation and technical excellence.\n What you’ll do (Role Expectations) \n \n Architect, develop, and optimize a low-latency, high-throughput AI Security plane utilizing Rust, specifically leveraging its async/await model for highly efficient I/O and service-oriented architecture\n Build resilient, distributed, and scalable systems, emphasizing concurrency, fault tolerance, and robust messaging protocols\n Implement and maintain gRPC services and APIs to ensure seamless integration of the AI Security plane with control and orchestration infrastructure\n Systematically enhance performance across the entire stack, including LLM models, by employing profiling tools for both kernel-space and user-space components\n Lead complex, multi-functional projects and initiatives, defining the technical roadmap and driving execution across teams\n \n Who You Are (Success Profile) \n \n You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.\n You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.\n You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.\n You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.\n You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.\n \n What We’re Looking for (Minimum Qualifications) \n \n 8+ years of software engineering experience\n Deep experience in systems programming using Rust, with a focus on asynchronous frameworks such as Tokio or async-std\n Proven ability to design and implement horizontally scalable, highly available, and observable distributed systems\n Strong command of Linux internals, including kernel-user space interaction, networking, sockets, and namespaces\n Skilled in performance instrumentation, containerized environments, Git workflows, and CI/CD pipelines\n \n What Will Make You Stand Out (Preferred Qualifications) \n \n Expert in systems languages such as C/C++ or Rust, with a focus on performance optimization\n Deep understanding of Linux networking stacks, Kubernetes networking, service meshes, and LLM model optimization\n ","salary_min":154000,"salary_max":220000,"location":"Bellevue, WA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["security","distributed-systems","api-design","llm","data-pipeline","agents"],"apply_url":"https://job-boards.greenhouse.io/zscaler/jobs/5146138007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T15:07:34Z","expires_at":"2026-06-29T14:09:19.468531Z","created_at":"2026-05-29T14:33:11.60717Z","updated_at":"2026-05-30T14:09:19.582996Z","company_name":"Zscaler","company_slug":"zscaler","company_logo_url":"https://www.google.com/s2/favicons?domain=zscaler.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/06abea54-0601-42e3-bb89-32ddb1ee619d"},{"id":"ceb7845a-f491-495f-b9ad-afc4cbf8eff5","company_id":"3029e985-56bf-4ac2-9ae1-df4cdd53b12f","title":"Sr. Software Development Engineer-AI Security","slug":"sr-software-development-engineer-ai-security-12d276fe","description":"About Zscaler \n Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.\n Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability.\n We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.\n Role \n We are looking for a Senior Software Development Engineer-AI Security to join us as a founding member of our AI Security Team. This is a Hybrid role based in San Jose, CA or Bellevue, WA (3 days in office), reporting to the Director of Software Engineering within the Emerging Tech org.\n You will build a high-reliability, low-latency AI security solution capable of scaling to hundreds of millions of users. In this role, you will be crucial in enhancing security capabilities for the AI within the world's largest cloud security platform by designing and implementing core infrastructure components and distributed systems while collaborating closely with stakeholders throughout the development lifecycle.\n What you’ll do (Role Expectations) \n \n Develop high-performance networking code for multiple desktop platforms using the Rust language and platform-native APIs\n Improve code quality through building solid, testable, and well-documented software foundations\n Design and implement major development projects with a focus on scalability, security, and performance\n Collaborate with product managers and cross-functional teams to deliver customer-impacting features\n Debug and solve complex network-related problems and enhance system functionality\n \n Who You Are (Success Profile) \n \n You thrive in ambiguity. You're comfortable building the path as you walk it. You thrive in a dynamic environment, seeing ambiguity not as a hindrance, but as the raw material to build something meaningful.\n You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. True ownership involves leveraging dynamic range: the ability to navigate seamlessly between high-level strategy and hands-on execution.\n You are a problem-solver. You love running towards the challenges because you are laser-focused on finding the solution, knowing that solving the hard problems delivers the biggest impact.\n You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.\n You are a learner. You have a true growth mindset and are obsessed with your own development, actively seeking feedback to become a better partner and a stronger teammate. You love what you do and you do it with purpose.\n \n What We’re Looking for (Minimum Qualifications) \n \n Bachelor’s degree in computer science, engineering, or a related field\n 3+ years of software engineering experience with deep expertise in the Rust programming language and familiarity with lower-level languages such as C/C++\n Strong knowledge of system and network programming including firewalls, VPNs, protocols, TCP/IP, UDP, DNS, QUIC, H/3, and proxies\n Familiarity with system concepts such as virtual memory, multi-threading, and system APIs, and familiarity with SLM and LLM models\n Excellent debugging and problem-solving skills in both networking and system-level contexts\n \n What Will Make You Stand Out (Preferred Qualifications) \n \n Familiarity with DevOps pipelines, VPN technologies, and a strong understanding of security protocols and standards\n Experience writing testable, low-complexity code with dependency injection and thorough documentation\n Proficiency in additional programming languages like Swift, Python, or comparable technologies; direct experience in validating AI-d","salary_min":112000,"salary_max":160000,"location":"Bellevue, WA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["mlops","data-pipeline","agents","security","llm","distributed-systems"],"apply_url":"https://job-boards.greenhouse.io/zscaler/jobs/5146134007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T14:55:45Z","expires_at":"2026-06-29T14:09:19.312884Z","created_at":"2026-05-29T14:33:11.44252Z","updated_at":"2026-05-30T14:09:19.425288Z","company_name":"Zscaler","company_slug":"zscaler","company_logo_url":"https://www.google.com/s2/favicons?domain=zscaler.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ceb7845a-f491-495f-b9ad-afc4cbf8eff5"},{"id":"6dc81f39-064c-435f-95c1-b6c70be6a1c5","company_id":"e8c9f3a5-9310-43f5-9341-321fe6d93a92","title":"Machine Learning Engineer, App SW","slug":"machine-learning-engineer-app-sw-73eaf56f","description":"About us    \n Founded in 2017, Wayve is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.\n Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.\n At Wayve, your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  \n Make Wayve the experience that defines your career!  \n The Role  \n As an  ML Engineer  within the Application Engineering team, you’ll lead critical initiatives that push the frontier of model-based autonomous driving—both in terms of core driving performance and feature-level intelligence such as personalisation, comfort, and collaboration.\n You’ll design and deliver ML-driven behaviors that scale from assisted to autonomous driving. Your work will span across model architecture, data pipelines, evaluation frameworks, and real-world deployment. You’ll collaborate deeply with AI Platform, Simulation, Robot SW and Model Release teams to build systems that are performant, adaptable, and ready for production.\n Responsibilities:\n \n Develop and improve end-to-end driving models with state-of-the-art performance, robustness, and generalization.\n Lead projects on personalized and collaborative driving, including behavior conditioning, comfort tuning, and user alignment.\n Build evaluation pipelines and metrics for both closed-loop and open-loop driving performance and product readiness.\n Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and feature-specific development.\n Influence architecture choices, training methodologies, and deployment pathways for production-scale learning systems.\n Collaborate cross-functionally across various teams to ensure integration and iteration velocity.\n Mentor senior engineers and shape the long-term technical direction across Autonomy.\n \n About you:  \n In order to set you up for success as a Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.  \n Essential\n \n Extensive and proven track record of shipping deep learning systems to production.\n Expert in deep learning (esp. sequential models, control, planning, or perception).\n Proficient in Python and other relevant languages (e.g. C++ and CUDA) and ML frameworks (esp. PyTorch), with a solid foundation in software engineering practices.\n Experience with real-time systems or robotics, ideally with simulation- or vehicle-in-the-loop components.\n Ability to lead technical initiatives across teams, drive alignment, and mentor engineers.\n \n Desirable\n \n Prior work in autonomous driving, imitation learning, or trajectory prediction.\n Familiarity with personalization, human behavior modeling, or driver intent inference.\n Experience integrating ML systems into production hardware or multi-agent simulation.\n \n This role is a full-time role based in Sunnyvale or Detroit (hybrid) and the reasonably estimated salary for this role ranges from $283,500 to $381,600, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.\n At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.  \n #LI-KM1 \n Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. \n We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition  (including breastfeeding) or any other ba","salary_min":283500,"salary_max":381600,"location":"Detroit","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","data-pipeline","robotics","pytorch","generative-ai","deep-learning","gpu","agents"],"apply_url":"https://wayve.firststage.co/jobs?gh_jid=8568694002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T14:51:17Z","expires_at":"2026-06-29T14:12:44.75073Z","created_at":"2026-05-29T14:50:38.39389Z","updated_at":"2026-05-30T14:12:44.866872Z","company_name":"Wayve","company_slug":"wayve","company_logo_url":"https://www.google.com/s2/favicons?domain=wayve.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6dc81f39-064c-435f-95c1-b6c70be6a1c5"},{"id":"23d134c7-f2bf-4c83-87f8-3938851bc707","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Senior Machine Learning Engineer","slug":"senior-machine-learning-engineer-583097ba","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n Anduril's Air \u0026 Missile Defense Radar team develops cutting-edge tracking algorithms and software systems that detect, track, and characterize airborne threats in real-time. We're building the next generation of tracking intelligence capabilities—automated analysis systems that understand tracking performance, identify failure modes, and continuously improve our algorithms through data-driven insights.\n This role sits at the intersection of ML engineering and tracking domain expertise. You'll build end-to-end pipelines that ingest tracking algorithm telemetry, analyze correlation failures and performance anomalies, train models to automate root cause analysis, and deploy production tools that help engineers ask questions like \"why didn't track X and track Y associate?\" We don't just track targets; we track our tracking systems and make them smarter.\n WHAT YOU'LL DO\n \n Own tracking intelligence infrastructure end-to-end : Build the platform for ingesting tracking algorithm telemetry (hypotheses, scores, gains, association decisions), feature engineering performance metrics, training analysis models, and deploying them into production\n Automate tracking analysis : Develop ML models that identify correlation failures, track quality degradation, and root causes for tracking anomalies—replacing manual deep-dive investigations with scalable automated insights\n Build autotuning capabilities : Create systems that recognize incoming data characteristics and automatically adjust tracking algorithm parameters, frame rates, and model configurations for optimal performance\n Design human-in-the-loop tools : Build interfaces and query services that let engineers ask natural questions about tracking behavior and get data-driven answers backed by your models\n Exploit tracking telemetry : Instrument C++ tracking algorithms with appropriate logging (working with platform engineers), then marshal that data into consistent formats for analysis and model training\n Deploy in constrained environments : Package and deploy models for air-gapped systems with no external connectivity, following security scanning requirements where ML models are treated as data artifacts\n Manage the ML lifecycle : Handle data catalogs, ground truth labeling, model registries, versioning, and validation—ensuring models improve tracking performance in measurable ways\n Bridge domains : Translate between tracking algorithm fundamentals (Kalman filters, data association, multi-hypothesis tracking) and ML/data science techniques to build solutions that actually work\n Drive make/build decisions : Evaluate when to build custom models vs. leverage existing ML capabilities, selecting appropriate algorithm architectures for tracking intelligence problems\n Work hands-on-keyboard : This is a one-person show initially—you'll architect, code, deploy, and iterate rapidly using modern Python-based ML tooling\n \n REQUIRED QUALIFICATIONS\n \n 3+ years of experience with a strong mix of ML engineering and data science—you've built models AND deployed them into production systems\n Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)\n Experience with MLOps practices: data pipelines, feature engineering, model versioning, experiment tracking, and deployment workflows\n Familiarity with ML infrastructure tooling (MLflow, Dagster/Airflow, or similar orchestration tools)\n Understanding of tracking, estimation, or filtering algorithms (Kalman filters, data association techniques)—you need to understand what tracking algorithms output and why they make the decisions they do\n Ability to work with streaming time-series data and engineer features from algorithm telemetry\n Experience building data catalogs, managing ground truth labels, and validating model performance\n Strong software engineering fundamentals—you can build maintainable, production-quality code independently\n Comfortable working in C++ environments enough to add instrumentation/logging (no deep algorithm development required)\n Ability to obtain and maintain a U.S. Top Secret SCI security clearance\n \n PREFERRED QUALIFICATIONS\n \n Experience deploying ML models in edge, embedded, or air-gapped environments with security constraints\n Background in def","salary_min":165000,"salary_max":218000,"location":"Fort Collins, CO","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["tensorflow","mlops","computer-vision","data-pipeline","pytorch","payments","machine-learning"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5126634007?gh_jid=5126634007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T21:29:38Z","expires_at":"2026-06-29T14:06:48.665653Z","created_at":"2026-05-28T14:08:23.033047Z","updated_at":"2026-05-30T14:06:48.786007Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/23d134c7-f2bf-4c83-87f8-3938851bc707"},{"id":"a81eda03-7e82-45be-919e-39f563f2c24d","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director, Prediction and ML Planning","slug":"director-prediction-and-ml-planning-ec32b5bd","description":"About Motional: \n Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation. Mission Summary: \n Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.\n As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion. Core Responsibilities: \n \n Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.\n Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. \n Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.\n Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards. \n \n Required Qualifications \u0026 Experience: \n \n Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.\n Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.\n ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.\n Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.\n Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs) .\n Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning. \n \n Preferred Qualifications: \n \n Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.\n A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.\n Experience building large-scale data pipelines and training infrastructure required to train large driving models.\n \n \n  We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote. \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Rang","salary_min":288000,"salary_max":396000,"location":"Pittsburgh, PA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","autonomous-vehicles","robotics","llm","data-pipeline"],"apply_url":"https://motional.com/open-positions/?gh_jid=7749537003#/7749537003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T14:37:33Z","expires_at":"2026-06-29T14:05:57.776906Z","created_at":"2026-05-28T14:07:27.895574Z","updated_at":"2026-05-30T14:05:57.889935Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a81eda03-7e82-45be-919e-39f563f2c24d"},{"id":"fa191a7a-632b-472c-acb7-b7360a7925f8","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director, Prediction and ML Planning","slug":"director-prediction-and-ml-planning-360f2a66","description":"About Motional: \n Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation. Mission Summary: \n Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.\n As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion. Core Responsibilities: \n \n Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.\n Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. \n Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.\n Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards. \n \n Required Qualifications \u0026 Experience: \n \n Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.\n Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.\n ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.\n Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.\n Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs) .\n Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning. \n \n Preferred Qualifications: \n \n Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.\n A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.\n Experience building large-scale data pipelines and training infrastructure required to train large driving models.\n \n \n  We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote. \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Rang","salary_min":288000,"salary_max":396000,"location":"Remote (US)","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["autonomous-vehicles","llm","reinforcement-learning","robotics","data-pipeline"],"apply_url":"https://motional.com/open-positions/?gh_jid=7749539003#/7749539003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T14:37:33Z","expires_at":"2026-06-29T14:05:57.689923Z","created_at":"2026-05-28T14:07:27.811425Z","updated_at":"2026-05-30T14:05:57.80649Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fa191a7a-632b-472c-acb7-b7360a7925f8"},{"id":"3fa85144-87ad-48b5-b151-9737480face6","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Director, Prediction and ML Planning","slug":"director-prediction-and-ml-planning-ecc5bb9c","description":"About Motional: \n Motional is a public transit and autonomous vehicle pioneer, developing Level 4 driverless vehicles that are changing the way the world moves. At the heart of our mission is the Autonomy organization, where we solve some of the most complex engineering and artificial intelligence challenges of our generation. Mission Summary: \n Motional is seeking a visionary, technically deep Director of Behaviors to lead our machine learning-based Prediction and Planning teams. In this role, you will sit at the intersection of intent forecasting and ego-vehicle decision-making. You will be directly responsible for leading multiple engineering sub-teams, setting the technical roadmap for our next-generation behavior stack, and pioneering the shift toward state-of-the-art end-to-end models that execute joint prediction and planning.\n As a senior leader in the Autonomy organization, you will not only drive technical breakthroughs but will also scale and nurture a world-class AI organization in a sustainable, inclusive, and highly collaborative fashion. Core Responsibilities: \n \n Strategic Leadership: Oversee and unify the machine learning-based Prediction and Motion Planning teams. Establish a clear, aggressive, yet sustainable technical roadmap that transitions our stack towards a unified (fully learnt) Large Driving Model performing joint prediction and planning.\n Technical Direction: Stay at the absolute frontier of AI research and define the technical roadmap for developing state-of-the-art imitation learning (IL) and reinforcement learning (RL) approaches to advance end-to-end learnt planning. Guide the team in exploring and incorporating modern paradigms like Vision-Language-Action models (VLAs) to improve the vehicle's semantic understanding, reasoning, and zero-shot generalization capabilities in complex urban environments. \n Organizational Growth: Lead, mentor, and scale multiple sub-teams of machine learning engineers and researchers. Implement sustainable engineering practices that prevent burnout, promote psychological safety, and ensure high technical velocity.\n Cross-Functional Collaboration: Partner closely with Perception, Infrastructure and Systems Engineering to ensure the Large Driving Model seamlessly integrates onto the vehicle platform and meets rigorous safety and real-time performance standards. \n \n Required Qualifications \u0026 Experience: \n \n Proven Leadership: 5+ years of experience managing high-performing engineering teams, with at least 3+ years of experience managing multiple sub-teams within an autonomous systems, robotics, or advanced AI organization.\n Sustainable Scaling: Demonstrated track record of growing an engineering organization sustainably—balancing technical debt, architectural scalability, and team well-being.\n ML Behavior Expertise: Deep theoretical and practical proficiency in machine learning applied to robotics behaviors. Advanced expertise in Imitation Learning and Reinforcement Learning for decision-making. Strong understanding of the full lifecycle from research to vehicle deployment.\n Unified Architectures: Proven experience guiding teams toward building integrated models (e.g., trajectory forecasting joint with ego-policy generation) rather than decoupled, sequential pipelines.\n Modern AI Paradigms: Strong familiarity with multimodal foundational AI models, specifically Vision-Language-Action models (VLAs) .\n Educational Background: M.S. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related quantitative field with a heavy focus on Machine Learning. \n \n Preferred Qualifications: \n \n Experience building and scaling up LLMs/VLMs/VLAs and successfully deploying to production.\n A strong footprint in the AI/robotics research community (CVPR, ICCV, NeurIPS, ICRA, IROS publications), with a willingness to publish future work.\n Experience building large-scale data pipelines and training infrastructure required to train large driving models. \n \n  We encourage a hybrid schedule with in-office time at one of our locations in Boston or Pittsburgh to support collaboration, or this role can be fully remote. \n The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.  \n Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. \n Salary Range","salary_min":288000,"salary_max":396000,"location":"Boston, MA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","reinforcement-learning","llm","autonomous-vehicles","robotics"],"apply_url":"https://motional.com/open-positions/?gh_jid=7749522003#/7749522003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T14:37:32Z","expires_at":"2026-06-29T14:05:57.612382Z","created_at":"2026-05-28T14:07:27.983518Z","updated_at":"2026-05-30T14:05:57.722175Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3fa85144-87ad-48b5-b151-9737480face6"},{"id":"4b838594-7738-4715-8dfb-17cd9c747ea8","company_id":"3029e985-56bf-4ac2-9ae1-df4cdd53b12f","title":"Principal GenAI Data Engineer ","slug":"principal-genai-data-engineer-9a655ea2","description":"About Zscaler \n Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.\n Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability.\n We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.\n Role \n We are looking for a Principal GenAI Data Engineer to join our IT Data Strategy team. This role is fully remote within the US, reporting to the Senior Manager, Enterprise AI Data Platform. We are seeking an experienced technical leader to drive the design and implementation of enterprise-grade Generative AI data ingestion, knowledge preparation, and platform architectures that enable scalable, production-ready GenAI applications. This role focuses on architecting robust pipelines and platforms for ingesting, processing, governing, and serving structured and unstructured enterprise data for AI/LLM workloads. The ideal candidate combines deep expertise in enterprise data architecture, unstructured data pipelines, GenAI platform engineering, and strong software engineering skills in Python.\n What you’ll do (Role Expectations) \n \n Architect enterprise-scale GenAI data platforms for ingestion, transformation, enrichment, and serving of structured and unstructured data\n Design scalable pipelines for enterprise knowledge ingestion from diverse data sources including documents, SaaS platforms, knowledge bases, collaboration tools, and databases\n Define architecture for metadata extraction, chunking, enrichment, embeddings generation, and knowledge preparation workflows\n Design AI-ready data models and storage strategies for vector, graph, and hybrid knowledge systems\n Architect scalable unstructured data processing pipelines for text, images, PDFs, tables, and multimodal content\n \n Who You Are (Success Profile) \n \n You act like an owner. Your passion for the mission fuels your bias for action. You operate with integrity because you genuinely care about the outcome. You adapt to what’s needed, navigating seamlessly between high-level strategy and hands-on execution.\n You are a problem-solver. You seek out challenges because you are energized by finding solutions, knowing that solving the hard problems delivers the biggest impact.\n You lead with integrity. You do the right thing, even when it’s hard. You hold yourself and others to a high standard of accountability and build trust by matching your words with consistent, transparent action.\n You think at scale. You connect your day-to-day work to the larger company mission and think globally. You build solutions, processes, and teams that are not just effective today but are built to last and support a high-growth, global organization.\n You are a high-trust collaborator. You are ambitious for the team, not just yourself. You embrace our challenge culture by giving and receiving ongoing feedback—knowing that candor delivered with clarity and respect is the truest form of teamwork and the fastest way to earn trust.\n \n What We’re Looking for (Minimum Qualifications) \n \n Expert-level Python programming and software engineering capabilities\n Experience building distributed/scalable data pipelines for AI workloads\n Strong understanding of unstructured data extraction and processing pipelines\n Experience with vector databases, graph databases, and metadata/knowledge storage systems\n Hands-on experience with clustering, entity recognition algorithms, and modern retrieval strategies (including RAG, search, and agentic AI workflows)\n \n What Will Make You Stand Out (Preferred Qualifications) \n \n Deep understanding of AI-ready data platform design principles and the ability to bridge platform/data engineering with GenAI/LLM application requirements\n Experience with LLMOps / GenAIOps frameworks such as LangSmith, Evaluation Framework like Arize","salary_min":182000,"salary_max":260000,"location":"Remote (US)","workplace":"hybrid","job_type":"full-time","experience_level":"principal","tags":["security","embeddings","data-pipeline","agents","generative-ai","llm","data-engineering"],"apply_url":"https://job-boards.greenhouse.io/zscaler/jobs/5142526007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T18:53:33Z","expires_at":"2026-06-29T14:09:18.592777Z","created_at":"2026-05-27T14:09:33.406845Z","updated_at":"2026-05-30T14:09:18.706338Z","company_name":"Zscaler","company_slug":"zscaler","company_logo_url":"https://www.google.com/s2/favicons?domain=zscaler.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4b838594-7738-4715-8dfb-17cd9c747ea8"},{"id":"5e52cfc4-669e-46bb-8b87-84c11248ba64","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Analytics Engineer","slug":"analytics-engineer-97634fa3","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Analytics Engineer - Consumer Data Science \n Check out our r/RedditEng post to learn more about the team, and what we do: https://www.reddit.com/r/RedditEng/comments/1mnmf71/analytics_engineering_reddit/  \n On Reddit, people can dive into anything through experiences built around their interests, hobbies, and passions. Our mission is to empower communities and make their knowledge accessible to everyone. With over 100,000 active communities and over 120 million daily active users, it is home to the most open and authentic conversations on the internet. Reddit’s unique and differentiated product is extremely attractive to advertisers, who can reach out to and connect to our users authentically.\n We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization, focused on the Consumer domain. We are looking for someone who can work closely with Data Scientists and members of Consumer cross-functional teams (Product, Engineering, and Design) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base.\n Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas.\n Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence.\n Responsibilities: \n \n Be an Analytics Engineering leader within the Consumer organization and a key contributor and collaborator to the success of Data Science data quality, performance, reliability, and automation initiatives.\n Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities.\n Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines.\n Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.\n Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service.\n Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners.\n Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.\n \n Qualifications: \n \n Degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics\n 4+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.\n Strong programming proficiency in Python, SQL, Spark, Scala, etc.\n Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data.\n Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering.\n Experience in data visualization and dashboard design.\n Deep understanding of technical and functional designs for relational and MPP Databases.\n Proven track record of cross-functional execution and collaboration. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen.\n Self-starter, ability to work independe","salary_min":164200,"salary_max":229900,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["agents","healthcare","data-pipeline","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/7958354","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T18:42:47Z","expires_at":"2026-06-29T14:08:29.565057Z","created_at":"2026-05-27T14:08:43.457817Z","updated_at":"2026-05-30T14:08:29.678303Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5e52cfc4-669e-46bb-8b87-84c11248ba64"},{"id":"77cc20d9-b485-408a-9a85-753c8c333d3c","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Software Engineer, App","slug":"senior-software-engineer-app-e60d648a","description":"Your Impact at LILA Scientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality — and we need engineers who want to solve problems no one has solved before.\n We're hiring Sr Principal / Principal Software Engineers to design the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI.\n About The Team \n The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results.\n \n AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons.\n The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them.\n You'll learn domains you never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your technical surface area grows fast.\n You'll ship things that matter. The tools you build accelerate research timelines from months to days.\n \n If you want to build at the intersection of AI and science, move fast without breaking trust, and grow into the kind of engineer who can architect systems that don't exist yet — we want to talk.\n \n What You'll Be Building \n \n Design \u0026 Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.\n Database Architecture \u0026 Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.\n Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.\n Performance \u0026 Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.\n Cloud \u0026 Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.\n Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.\n \n What You'll Need To Succeed \n \n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.\n 5-8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.\n Full Stack Development : Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)\n Hands on experience using AI coding assistants to drive productivity is required.\n Communication \u0026 Collaboration : Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.\n Problem Solving : Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.\n \n Bonus Points For \n \n Applied AI Engineering: Experience building with AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks.\n Cloud \u0026 DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).\n Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).\n Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).\n Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).\n Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.\n Experience with laboratory devices, robotics, or hardware drivers.\n \n \n Compensation \n We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.\n U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.\n International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to","salary_min":144000,"salary_max":240000,"location":"Boston, MA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["agents","pytorch","robotics","data-pipeline","llm","embeddings","cloud","rag"],"apply_url":"https://job-boards.greenhouse.io/lilasciences/jobs/4248042009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:55:46Z","expires_at":"2026-06-29T14:17:43.519875Z","created_at":"2026-05-27T14:18:34.581118Z","updated_at":"2026-05-30T14:17:43.627321Z","company_name":"Lila Sciences","company_slug":"lila-sciences","company_logo_url":"https://www.google.com/s2/favicons?domain=lila.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/77cc20d9-b485-408a-9a85-753c8c333d3c"},{"id":"a5d985bb-042b-4ab6-9059-b7941fc36fcc","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior People Data Scientist","slug":"senior-people-data-scientist-4ff4247c","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n Instacart’s People Analytics \u0026 Research (PAR) team delivers trusted insights that help leaders make better, faster decisions and create an environment where every employee can do the best work of their career. Embedded within People Services Delivery , we partner across the People org and the business to build the data infrastructure, dashboards, analytical frameworks and research that power workforce planning, organizational health, and strategic HR initiatives for all Instacart employees. In addition, our mission is to bring these insights to life through close partnerships with partner teams across Instacart. \n We’re hiring a Senior People Data Scientist (L5) to serve as an enterprise‑wide people analytics thought partner—blending data engineering, analytics, consulting, and data product ownership . You will own complex, multi‑quarter analytical workstreams, shape company‑level people metrics, and help leaders at all levels use data to make better, more equitable decisions about our workforce.\n This is a high‑visibility IC role with significant exposure to senior HR and business leaders, ideal for someone who is equally comfortable in Snowflake, extracting insights from employee data, executive‑level storytelling, and in shaping how HR and business leaders across Instacart use data at scale. \n About the Job \n \n Help to evolve the enterprise people analytics agenda across key domains (e.g., organizational health, performance, hiring), including cross functional partnerships to align metrics to Instacart’s priorities and providing insights which help solve our more complex people problems.\n Contribute to high‑stakes, enterprise‑wide projects , such as:\n \n Drivers of retention across functions\n Implementation and analysis of people surveys across Instacart\n Organizational Health and design metrics\n Engagement survey insights and action effectiveness\n Implementation of AI in analysis workflows\n \n Design and mature self‑serve people data products (dashboards, standardized views, metric layers) that scale across HR and the business—standardizing definitions, partnering with People Tech and Finance on data architecture, and driving adoption through enablement and training.\n Own Data Warehousing and Data Architecture design decisions spanning across data ingestion, ETL/ELTs through BI Tools and LLMs.\n Bring analytical rigor to enterprise People programs (e.g., performance cycles, comp reviews, workforce planning, AES) by defining success metrics, segmenting impact, and recommending changes based on evidence and HRBP‑style judgment about feasibility and change management.\n Apply and interpret advanced methods where needed , such as predictive attrition models, cohort/survival analysis, and simple causal frameworks to evaluate program effectiveness, while keeping methods transparent and explainable to HR and business audiences.\n Serve as a partner to HRBPs, People leaders, and analysts on data literacy, metric interpretation, and responsible use of HR data. Contribute meaningfully to the team’s move from ad hoc requests to thought partnership and guidance on the appropriate use of people data for decision making.\n Champion data governance, privacy, and role‑based access across Workday, Snowflake, BI tools, and Qualtrics, partnering with People Tech and vendors to ensure HR data is accurate, secure, and fit for sensitive people decisions.\n Contribute to PAR’s roadmap, operating model, and culture —refining intake and prioritization, setting bar‑raising standards for analysis and storytelling.\n \n About You \n Minimum Qualifications \n \n 5+ years of experience in analytics, data science, business intelligence, or a closely related field, with at least 2–3+ years in People Analytics / HR data (HCM, recruiting, comp, retention, DEI, engagement, or","salary_min":161000,"salary_max":170000,"location":"Remote (Canada)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","llm","nlp","data-science"],"apply_url":"https://instacart.careers/job/?gh_jid=7958122","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:51:46Z","expires_at":"2026-06-29T14:08:41.826643Z","created_at":"2026-05-27T14:08:55.940238Z","updated_at":"2026-05-30T14:08:41.93919Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a5d985bb-042b-4ab6-9059-b7941fc36fcc"},{"id":"17bd9f6c-5e16-4fde-b4a9-69edd1d0b893","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior People Data Scientist","slug":"senior-people-data-scientist-7d166767","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview \n Instacart’s People Analytics \u0026 Research (PAR) team delivers trusted insights that help leaders make better, faster decisions and create an environment where every employee can do the best work of their career. Embedded within People Services Delivery , we partner across the People org and the business to build the data infrastructure, dashboards, analytical frameworks and research that power workforce planning, organizational health, and strategic HR initiatives for all Instacart employees. In addition, our mission is to bring these insights to life through close partnerships with partner teams across Instacart. \n We’re hiring a Senior People Data Scientist (L5) to serve as an enterprise‑wide people analytics thought partner—blending data engineering, analytics, consulting, and data product ownership . You will own complex, multi‑quarter analytical workstreams, shape company‑level people metrics, and help leaders at all levels use data to make better, more equitable decisions about our workforce.\n This is a high‑visibility IC role with significant exposure to senior HR and business leaders, ideal for someone who is equally comfortable in Snowflake, extracting insights from employee data, executive‑level storytelling, and in shaping how HR and business leaders across Instacart use data at scale. \n About the Job \n \n Help to evolve the enterprise people analytics agenda across key domains (e.g., organizational health, performance, hiring), including cross functional partnerships to align metrics to Instacart’s priorities and providing insights which help solve our more complex people problems.\n Contribute to high‑stakes, enterprise‑wide projects , such as:\n \n Drivers of retention across functions\n Implementation and analysis of people surveys across Instacart\n Organizational Health and design metrics\n Engagement survey insights and action effectiveness\n Implementation of AI in analysis workflows\n \n Design and mature self‑serve people data products (dashboards, standardized views, metric layers) that scale across HR and the business—standardizing definitions, partnering with People Tech and Finance on data architecture, and driving adoption through enablement and training.\n Own Data Warehousing and Data Architecture design decisions spanning across data ingestion, ETL/ELTs through BI Tools and LLMs.\n Bring analytical rigor to enterprise People programs (e.g., performance cycles, comp reviews, workforce planning, AES) by defining success metrics, segmenting impact, and recommending changes based on evidence and HRBP‑style judgment about feasibility and change management.\n Apply and interpret advanced methods where needed , such as predictive attrition models, cohort/survival analysis, and simple causal frameworks to evaluate program effectiveness, while keeping methods transparent and explainable to HR and business audiences.\n Serve as a partner to HRBPs, People leaders, and analysts on data literacy, metric interpretation, and responsible use of HR data. Contribute meaningfully to the team’s move from ad hoc requests to thought partnership and guidance on the appropriate use of people data for decision making.\n Champion data governance, privacy, and role‑based access across Workday, Snowflake, BI tools, and Qualtrics, partnering with People Tech and vendors to ensure HR data is accurate, secure, and fit for sensitive people decisions.\n Contribute to PAR’s roadmap, operating model, and culture —refining intake and prioritization, setting bar‑raising standards for analysis and storytelling.\n \n About You \n Minimum Qualifications \n \n 5+ years of experience in analytics, data science, business intelligence, or a closely related field, with at least 2–3+ years in People Analytics / HR data (HCM, recruiting, comp, retention, DEI, engagement, or","salary_min":161000,"salary_max":170000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["nlp","llm","data-pipeline","data-science"],"apply_url":"https://instacart.careers/job/?gh_jid=7958121","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T16:49:45Z","expires_at":"2026-06-29T14:08:41.750936Z","created_at":"2026-05-27T14:08:56.031655Z","updated_at":"2026-05-30T14:08:41.861595Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/17bd9f6c-5e16-4fde-b4a9-69edd1d0b893"}],"page":1,"per_page":20,"total":1201,"total_pages":61}