{"has_next":true,"jobs":[{"id":"c47d445d-a8c4-46a7-815e-584f4ff1b92b","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Research Scientist - Frontier Benchmarks","slug":"research-scientist-frontier-benchmarks-83166d4b","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 \n \n ABOUT THE ROLE  \n We're looking for a Research Scientist to collaborate with partners and lead the development of the next frontier benchmarks and datasets. This is a highly visible, customer-facing role at the intersection of research, company strategy, and go-to-market. You'll design datasets taking into account frontier model performance and work with our academic partners, and then partner with delivery, product and go-to-market to scale out production. You will also  serve as a credible technical partner for our customers, prospects, and drive results that impact the broader research community. \n This role reports directly to the Head of Research and is ideal for someone who is energized by cross-functional work and wants to understand how startups operate across research, data operations, and commercial teams. \n MAIN RESPONSIBILITIES  \n \n Design state of the art datasets that drive frontier model training and evaluation based on current model performance and academic partnerships \n Translate benchmark insights into clear, compelling narratives that articulate the ROI of expert-curated data for customer-facing presentations, technical reports, and go-to-market materials.\n Work cross-functionally with data operations, product, engineering, and strategy to surface research findings that inform the company roadmap. \n Stay at the frontier of LLM evaluation research and bring best practices into Snorkel's workflows\n Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements that advance the conversation around data-centric AI\n \n PREFERRED QUALIFICATIONS  \n \n Strong research background in AI/ML evaluation, NLP, or related fields, with a track record of rigorous experimental design — especially around measuring the impact of training and evaluation data on model behavior. \n Exceptional communication skills — able to present complex technical findings clearly to both technical and non-technical audiences \n Comfort operating in a fast-moving, cross-functional environment with ambiguous problem spaces \n Genuine interest in GTM strategy, startup dynamics, and the commercial side of AI data services. \n Ph.D. in machine learning, NLP, or a related field preferred; equivalent industry or research lab experience considered.\n \n \n  \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 harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. \n We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.","salary_min":200000,"salary_max":325000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["llm","generative-ai","nlp","research"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6009489004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T21:19:29Z","expires_at":"2026-06-29T14:03:05.663367Z","created_at":"2026-05-30T14:03:05.781019Z","updated_at":"2026-05-30T14:03:05.781019Z","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/c47d445d-a8c4-46a7-815e-584f4ff1b92b"},{"id":"73600478-6692-47ce-be77-2aebfb5bb4a2","company_id":"82d2abc2-444c-4d89-9646-4739e72d700d","title":"Machine Learning Engineer","slug":"machine-learning-engineer-5aefaff6","description":"About Checkr Checkr is building the data platform to power safe and fair decisions. Over 140,000 companies and millions of people rely on Checkr for AI verification in the moments that matter most: getting a new job, a new place to live, a car ride, childcare, even a date. Customers include Uber, Pennymac, Airbnb, Doordash, Amazon, and Anthropic. We’re a team that thrives on solving complex problems with innovative solutions that advance our mission. Checkr is recognized on Forbes Cloud 100 2025 List and is a Y Combinator 2024 Breakthrough Company .\n About the team/role \n We’re hiring an ML Engineer (P2) to build and ship the AI systems that power Checkr’s core products. This role sits on the ML team inside Checkr’s Data \u0026 ML organization within Engineering.\n Checkr runs millions of background checks a year. The ML team builds the systems that make those checks faster, more accurate, and cheaper to operate: document processing, charge classification, entity resolution, and in-product intelligence. These are production services that Product Engineering depends on daily.\n This is not a research role or a notebook role. You’ll own ML services end-to-end: design them, code them, deploy them, monitor them. We need someone who writes production software, builds with LLMs and APIs as first-class tools, and can tell the difference between working code and AI slop. If you’ve spent the last few years building AI-native software and you care deeply about engineering craft, we want to talk.\n This role sits in the central Data \u0026 ML team within the Engineering organization. You will partner daily with Product Engineering, Product, and cross-functional teams. You’ll also contribute to Checkr’s broader AI strategy, including our initiative to deploy our agentic fleet and build scalable context with our semantic layer.\n We are looking for someone based in San Francisco who has built ML systems in fast-moving, impact-first environments. Less process, more shipping. Less paperwork, more results.\n  \n What you’ll do \n \n Build and deploy ML/AI services. Design, develop, and ship ML models and AI systems that Product Engineering teams rely on. You write the model code, the API layer, the monitoring, and the tests. Not notebooks; production services.\n Design with LLMs and APIs. Use LLM APIs (OpenAI, Anthropic, etc.) as building blocks in production systems. You know when to call an LLM, when to fine-tune, when to use a classical model, and when to write a rule. You think about cost, latency, and quality together.\n Ship production software. Write clean, well-structured code with solid OOP, proper abstractions, error handling, and tests. Your code gets reviewed by SWEs and passes. CI/CD is how you work, not something you bolt on at the end.\n Partner with product and engineering. Translate business problems into ML solutions. Define API contracts with product engineers. Explain your approach clearly to non-ML partners and leave the room with alignment, not confusion.\n Evaluate and iterate fast. Build evaluation frameworks, run experiments, and make data-driven decisions about model and system performance. Ship and iterate; don’t wait for perfect.\n Ship AI-powered workflows. Put AI to work on your own processes: automate pipelines, build agentic workflows, and contribute reusable skills and context to Checkr’s agentic platform. The expectation is that our teams operate AI-first.\n \n What you bring \n \n A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field, or equivalent depth from experience\n 4+ years building software professionally, with at least 2 of those building ML systems that run in production\n Strong Python fluency; you write clean, testable, well-structured code with solid OOP instincts. Not scripts; software\n Hands-on experience using LLM APIs in production systems: prompt engineering, structured outputs, function calling, cost management, and evaluation\n You’ve built and maintained APIs, worked with CI/CD pipelines, and shipped code that other engineers depend on\n Comfortable with distributed systems concepts: queues, async processing, caching, horizontal scaling\n Experience with NLP tasks in production: classification, extraction, entity resolution, summarization\n Comfort with and enthusiasm for AI-assisted workflows; experience using LLMs, code-generation tools, or agentic systems in production or operational contexts is a strong signal\n You can evaluate tradeoffs: fine-tune vs. prompt, hosted vs. self-deployed, classical ML vs. LLM, rule vs. model\n Strong communication skills; you explain technical decisions clearly to engineers and non-engineers alike, without hiding behind jargon\n You use AI tools (Copilot, Claude, etc.) to move faster, but you understand every line they produce. You can spot AI slop and you don’t ship it\n An A-player mindset with a strong bias for action: you raise the bar, move with urgency, stay resilient through ambiguity, and t","salary_min":168000,"salary_max":198000,"location":"San Francisco, CA","workplace":"onsite","job_type":"full-time","experience_level":"mid","tags":["nlp","code-generation","mlops","agents","payments","legal","distributed-systems","llm"],"apply_url":"https://job-boards.greenhouse.io/checkr/jobs/7966920","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-29T15:17:56Z","expires_at":"2026-06-29T14:10:31.076983Z","created_at":"2026-05-30T14:10:31.19215Z","updated_at":"2026-05-30T14:10:31.19215Z","company_name":"Checkr","company_slug":"checkr","company_logo_url":"https://www.google.com/s2/favicons?domain=checkr.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/73600478-6692-47ce-be77-2aebfb5bb4a2"},{"id":"b2263952-2d61-4a59-acd2-4d8506c9b16e","company_id":"cf6855a4-6591-475f-be10-f3f36cf31758","title":"Senior Software Engineer, Search Relevance","slug":"senior-software-engineer-search-relevance-8f221ba2","description":"WHAT IS BOX?  \n Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia.\n By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift.\n WHY BOX NEEDS YOU \n The Search Relevance team at Box powers discovery across billions of files, enabling customers to find the right content quickly, securely, and intelligently. As we expand into a new era of AI-powered content understanding, we’re investing in the foundation that makes great search possible: reliable systems, strong signals, and models that learn from real-world usage.\n This is a rare opportunity to work at the intersection of information retrieval science, applied machine learning, and large-scale distributed systems. You’ll be building the infrastructure that powers intelligent content discovery for Fortune 500 companies—where milliseconds matter, relevance is measurable, and your experiments directly impact how millions of users work.\n We’re looking for a Senior Software Engineer to elevate search quality end-to-end—signals, ranking, retrieval, and evaluation—while building scalable, low-latency services that serve queries in real time. You’ll partner with Product, Data, and Infra teams to productionize cutting-edge models and experimentation frameworks, and help define the future of Box’s content intelligence, including hybrid and semantic search and our next-generation content agent.\n WHAT YOU'LL DO  \n \n Build and improve ranking, retrieval, and recommendation systems; identify the right signals and metrics to drive quality improvements that users can feel.\n Apply cutting-edge techniques (embeddings, LLM-enabled retrieval, hybrid search) to productionize experimentation and evaluation pipelines that scale to trillions of documents.\n Define and execute offline/online evaluation, A/B testing, and relevance tuning (NDCG, MRR, precision@k) to continuously improve search outcomes.\n Develop infrastructure for low-latency, high-availability query serving and near real-time indexing across distributed systems.\n Tackle distributed systems challenges including data sharding, intelligent routing, replication, and performance optimization.\n From ETL pipelines and feature engineering to model serving and result ranking—understand how data flows through the system and optimize at every stage.\n Lead design and implementation of new platform components from the ground up; establish patterns, raise the bar on code quality, and champion best practices.\n Share your expertise, contribute to technical direction, conduct thoughtful code reviews, and help shape our engineering culture.\n Participate in our on-call rotation, available at all times while on-call to help respond to and triage any issues that arise.\n \n WHO YOU ARE  \n \n 5+ years of industry experience building and operating backend or distributed systems at scale.\n Strong proficiency in an object-oriented language (e.g., Java, Scala, C++, or Python); Python experience strongly preferred.\n Hands-on experience building ranking, recommendation, NLP, or applied AI platforms in production. You understand the ML lifecycle from training to serving.\n Comfortable with data pipelines, message queues, and/or streaming systems (e.g., Kafka, Pub/Sub) and near real-time data processing.\n Experienced deploying and operating microservices in cloud environments; solid grasp of reliability, observability, and performance best practices.\n BS in Computer Science or related field, or equivalent practical experience.\n AI-first mindset—pragmatic about using the right models, signals, and evaluation methods to improve outcomes quickly and measurably.\n \n PREFERRED \n \n Experience with Elasticsearch, Solr, Lucene, or building custom search systems; deep understanding of inverted indexes, scoring functions, and query optimization.\n Knowledge of ML relevance tuning, learning-to-rank, retrieval evaluation metrics, offline/online testing, and A","salary_min":198500,"salary_max":248000,"location":"Redwood City, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["search","tensorflow","distributed-systems","pytorch","llm","nlp","fine-tuning","mlops"],"apply_url":"https://job-boards.greenhouse.io/boxinc/jobs/7926452","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T19:12:52Z","expires_at":"2026-06-29T14:19:20.83221Z","created_at":"2026-05-29T15:11:42.002134Z","updated_at":"2026-05-30T14:19:20.940887Z","company_name":"Box","company_slug":"box","company_logo_url":"https://www.google.com/s2/favicons?domain=box.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b2263952-2d61-4a59-acd2-4d8506c9b16e"},{"id":"88b5244c-2383-4f06-b5ef-0ade11296098","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Technical Lead Manager, Prediction \u0026 Planning, Machine Learning Eval","slug":"staff-technical-lead-manager-prediction-planning-ml-eval-29b43259","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The Predictive Planning team (PrePlan) develops and deploys state-of-the-art machine learning solutions that predict the future state of the world and plan the Waymo Driver’s behavior. Our mission is to transform Waymo's unprecedented scale of driving data into robust, generalizable, and performant deep neural networks. These models enable the autonomous vehicle to navigate complex environments safely and efficiently. \n We have an exciting opportunity for a Staff Technical Lead Manager to lead our ML Evaluation team. In this role, you will define the strategic vision for our evaluation platforms, scaling the critical infrastructure and metrics required, and partner closely with the modeling teams to rigorously validate our next-generation deep neural networks and accelerate ML developer velocity across PrePlan.\n You will: \n \n Influence the strategic direction of foundational infrastructure and evaluation platforms to robustly support next-generation ML model evaluation use cases\n Collaborate cross-functionally with ML engineers, data scientists, and infrastructure teams to identify, define, and surface critical signals on model, component, and system-level performance\n Leverage and scale evaluation and infrastructure platforms to significantly enhance the ML developer experience, enabling faster iteration through earlier, more reliable, and trusted model evaluation\n Manage and mentor a focused team of engineers, aligning their career growth and aspirations with critical organizational needs\n Drive best practices and leverage deep technical awareness of the Alphabet ML stack (e.g., TensorFlow, JAX, Flax, Apache Beam) to optimize evaluation workflows\n Stay at the forefront of emerging technologies, industry trends, and research in ML evaluation methodologies and advanced metrics design\n \n You have:  \n \n M.S. in Computer Science, Mathematics, or equivalent industry experience in Robotics or large-scale ML systems with critical evaluation needs\n 5+ years of experience building and maintaining large-scale distributed infrastructure, ML inference systems, or evaluation platforms, including 3+ years of engineering management experience\n Strong coding and testing proficiency, specifically in Python and C++\n Strong foundational knowledge of model evaluation and core data science principles (e.g., confidence intervals, outlier identification, curve fitting, and causality analysis)\n Familiarity with large-scale ML deployment and orchestration tools (e.g., TF Serving, TorchServe, Kubeflow, SageMaker Pipelines, or Vertex AI Pipelines)\n Understanding of machine learning fundamentals and experience with popular ML frameworks such as JAX, PyTorch, or TensorFlow\n \n We prefer: \n \n Experience developing and maintaining evaluation pipelines for ML models\n Experience deploying and supporting machine learning models for computer vision, natural language processing, robotics/motion planning, or recommendation systems\n Experience supporting a small team of MLEs developing high-capacity, production-grade models and components\n Strong understanding of metrics computation and regression detection at scale\n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["robotics","nlp","computer-vision","pytorch","autonomous-vehicles","deep-learning","tensorflow","evaluation"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=7963516","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T17:26:50Z","expires_at":"2026-06-29T14:04:32.30248Z","created_at":"2026-05-29T14:12:24.077985Z","updated_at":"2026-05-30T14:04:32.417838Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/88b5244c-2383-4f06-b5ef-0ade11296098"},{"id":"0ed6f2c3-8d05-4541-a58a-3bc3eb48b078","company_id":"1a3abe34-d1c1-45b9-9259-3e2e007a961c","title":"Staff Research Scientist","slug":"staff-research-scientist-6193df9d","description":"About Voyage AI Team at MongoDB\n Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions.\n Position Overview\n We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks.\n This role can be based out of our Palo Alto office, or remotely in the United States.\n Responsibilities\n \n Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers\n Innovate in next-generation information retrieval and LLM agent paradigm\n Collaborate closely with other research scientists and research engineers as well as peers across the organization\n \n Qualifications\n \n PhD degree in Computer Science or related field\n A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues\n Strong background in machine learning, deep learning, and natural language processing\n Experience building complex neural networks for language and visual understanding\n Capable of conducting rigorous empirical studies to validate theoretical results\n Excellent leadership, problem-solving, and communication skills\n \n What We Offer\n \n Opportunity to work on real-world problems at the cutting edge of AI research\n Opportunity to utilize research vision to innovate the entire company and make real-world impact\n Exposure to the full lifecycle of AI model development, from research to production\n Our compensation (base + equity) for this position is competitive with frontier AI labs\n \n About MongoDB \n MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.\n With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.\n Our compass at MongoDB is our  Leadership Commitment,  guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.\n To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone.  From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys.  Learn more about what it’s like to work at MongoDB , and help us make an impact on the world!\n MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.\n MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.\n Req ID: 2273454547\n MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to ","salary_min":151000,"salary_max":297000,"location":"Palo Alto, CA","workplace":"onsite","job_type":"full-time","experience_level":"lead","tags":["nlp","computer-vision","search","llm","embeddings","deep-learning","research"],"apply_url":"https://www.mongodb.com/careers/job/?gh_jid=7956670","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-28T17:21:23Z","expires_at":"2026-06-29T14:08:48.853182Z","created_at":"2026-05-29T14:32:41.960202Z","updated_at":"2026-05-30T14:08:48.964003Z","company_name":"MongoDB","company_slug":"mongodb","company_logo_url":"https://www.google.com/s2/favicons?domain=www.mongodb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0ed6f2c3-8d05-4541-a58a-3bc3eb48b078"},{"id":"41b3afd9-e8d0-4d82-9e8e-9149ad7c9147","company_id":"0bedcaf4-210e-4f52-95d5-a82be8aff446","title":"Sr Machine Learning Engineer, AI Research","slug":"sr-machine-learning-engineer-ai-research-866a2680","description":"Join the company that’s building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world’s biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what’s next.\n We’re one of the fastest‑growing private companies and a leading player in a massive, fast‑moving market. With a global workforce, we’re remote‑first and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd.\n Why You'll Love This Role \n You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems.  You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers.\n On top of it all you will have fun. \n Cribl strives to be a great place to work for everyone.\n As An Active Member Of Our Team, You Will... \n \n Design, train, and evaluate machine learning models across a range of research and applied AI initiatives\n Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements\n Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems\n Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation\n Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation\n Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team\n Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them\n This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones\n \n If You've Got It - We Want It \n \n Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 4+ years of industry or research experience (Master's or PhD a plus)\n Deep hands-on experience training and evaluating ML models, including language models\n Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow\n Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights \u0026 Biases, Kubeflow, or similar)\n Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques\n Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize\n Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders\n \n #LI-Tag #LI-Remote\n The salary for this role is dependent on geographic location and will be based on the individual candidate's job-related knowledge, skills, and experience. In addition to base salary, for sales and some sales-adjacent roles, employees are eligible to earn incentive compensation (commission). For all other roles, employees are eligible to participate in the Cribl Corporate Bonus Program. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), and equity.\n Base Salary Range\n $185,000 — $215,000 USD \n Bring Your Whole Self Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We’re building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying. \n Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you’ll ever meet at cribl.io/about-us .","salary_min":185000,"salary_max":215000,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["nlp","tensorflow","computer-vision","mlops","pytorch","reinforcement-learning","fine-tuning","research"],"apply_url":"https://cribl.io/job-detail/?gh_jid=5979543004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-27T18:02:31Z","expires_at":"2026-06-29T14:18:07.512926Z","created_at":"2026-05-28T14:19:42.491471Z","updated_at":"2026-05-30T14:18:07.623902Z","company_name":"Cribl","company_slug":"cribl","company_logo_url":"https://www.google.com/s2/favicons?domain=cribl.io\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/41b3afd9-e8d0-4d82-9e8e-9149ad7c9147"},{"id":"84366e11-6b70-4a34-a8c9-d03cd29bd00e","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer","slug":"senior-applied-research-engineer-a868acf4","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 5+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":166900,"salary_max":225900,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["nlp","generative-ai","rag","embeddings","search","llm","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/fab401cd-087e-4b69-8a62-f0dbae4906c9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T22:59:45.262Z","expires_at":"2026-06-29T14:13:57.168877Z","created_at":"2026-05-27T14:14:33.203504Z","updated_at":"2026-05-30T14:13:57.34909Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/84366e11-6b70-4a34-a8c9-d03cd29bd00e"},{"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"},{"id":"96ba0be2-0b27-42c5-bc86-c4ffbb0b4359","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Applied Research Engineer","slug":"applied-research-engineer-8d39811c","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking an Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 3+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 1+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research workflow","salary_min":145200,"salary_max":196400,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"mid","tags":["rag","generative-ai","embeddings","search","llm","nlp","agents","healthcare"],"apply_url":"https://jobs.ashbyhq.com/drata/51a418d1-c371-4f9f-b248-2c3b542bec42/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:47.784Z","expires_at":"2026-06-29T14:13:57.088082Z","created_at":"2026-05-27T14:14:33.116975Z","updated_at":"2026-05-30T14:13:57.199158Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/96ba0be2-0b27-42c5-bc86-c4ffbb0b4359"},{"id":"cb6155b3-db5f-4d05-a1db-f321ee0718be","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Senior Applied Research Engineer 2","slug":"senior-applied-research-engineer-2-fcdd01a9","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata is seeking a Senior Applied Research Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with AI and Software Engineers to turn validated approaches into production-ready systems.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and more all depend on high-quality information retrieval and reasoning.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 6+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems\n\n - 2+ years of hands-on experience building or contributing to production AI/ML systems\n\n - Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance\n\n - Experience with RAG systems: chunking strategies, vector databases, retrieval optimization\n\n - Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance\n\n - Strong Python skills and comfort with notebook-driven research wo","salary_min":192000,"salary_max":259800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"senior","tags":["rag","llm","generative-ai","healthcare","nlp","agents","embeddings","search"],"apply_url":"https://jobs.ashbyhq.com/drata/e66701e1-f52f-471b-9bcc-400e874c651c/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:24:39.187Z","expires_at":"2026-06-29T14:13:56.779385Z","created_at":"2026-05-27T14:14:32.761406Z","updated_at":"2026-05-30T14:13:56.891705Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cb6155b3-db5f-4d05-a1db-f321ee0718be"},{"id":"4ed2ca6e-f534-411e-b47e-bc955d32008f","company_id":"238f4b8f-1e78-4053-9068-017564d76785","title":"Staff Applied Research Engineer","slug":"staff-applied-research-engineer-b2f192cc","description":"Our Mission \u0026 Values:\nAt Drata, we help companies earn and keep the trust of their users, customers, partners, and prospects. We’re the proof layer that shows great companies deserve the trust they aim to build.\n\nWe live our values every day. Built on Trust means consistency is everything. Act with Integrity by always doing the right thing. Being Customer-Obsessed keeps the people we serve at the center of our work. Competitive Fire drives us to push ourselves harder than anyone else. Diversity brings unique perspectives that lead to better solutions. Automation First ensures we save time and money by making efficiency a priority.\n\nOur Culture \u0026 Work Style 🚀\n\nAt Drata, we’re not just building software - we’re building a mindset. Everything we do springs from:\n\n - Be a Driver (Owner‑Operator Mentality): Own your work. Improve relentlessly. Deliver results.\n\n - Move at Drata Speed (Precision \u0026 Velocity): Fast decisions. Quick learning. Immediate impact.\n\n - Stay Mission-Driven (Customer‑Obsessed): Challenge assumptions. Deliver value. Stay hungry.\n\nWe pair that high-velocity culture with a thoughtful hybrid model because we believe flexibility and collaboration both matter. That’s why in the Bay we come together in-office Tuesday through Thursday our high‑impact collaboration days where teams align, strategize, and innovate. Mondays and Fridays are flexible, giving you space for focused work, balance, and autonomy.\n\nIf you thrive when you’re empowered, energized, and working with smart, mission-driven people, you’ll feel at home here.\n\nWhy Join The Drata Team?\n\nThe best way to understand the Driver’s Mindset is to see it in action. We’re an award-winning, mission-driven team of 600+ people worldwide, united by a culture that values trust, speed, and continuous growth.\n\n - See the Speed: https://www.youtube.com/watch?v=QidTdkGwKMY Watch our CEO, Adam Markowitz, discuss the hyper-growth journey, from $0 to $100M ARR in just four years\n\n - Hear the Voice of the Team https://drata.com/about/life-at-drata: Explore our \"Life at Drata\" page for employee testimonials on our collaborative and the growth opportunities available.\n\n - Experience the Impact https://www.greatplacetowork.com/certified-company/7044563: See why we are consistently recognized on Fortune's Best Workplaces lists.\n\n - Connect with Us on Socials: LinkedIn https://www.linkedin.com/company/drata/posts/?feedView=all - follow us for company updates, employee stories, and career news.\n\nJob Summary:\n\nDrata, at the vanguard of compliance software innovation and renowned for its commitment to trust and security across the internet, is on an ambitious path to redefine how AI and General AI technologies bolster compliance automation.\n\nDrata is seeking an Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous research, experimentation, and evaluation. In this role, you will optimize retrieval strategies, build evaluation frameworks, and establish the scientific foundation that enables our AI features to deliver accurate, trustworthy results.\n\nThis is a research-focused role emphasizing experimentation and rigor over production engineering. You'll work closely with AI Engineers handing off validated approaches for them to productionize while owning the quality metrics and evaluation systems that ensure our AI delivers on its promises.\n\nDrata's compliance platform is document-heavy: VRM Agent, AIQA, Trust Agent, policy-to-control mappers, and regulatory summarization all depend on retrieving the right information from large document sets. Your work will directly impact how well our AI understands and navigates compliance artifacts.\n\nWhat you'll do:\n\n - Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, structured retrieval, tool use, and multi-step workflows\n\n - Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements)\n\n - Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and weak supervision\n\n - Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection\n\n - Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions\n\n - Run experiments to validate hypotheses and quantify improvements before production rollout\n\n - Debug failure modes and build error taxonomies across retrieval, reasoning, and generation\n\n - Collaborate with AI and Software Engineers to hand off validated approaches for productionization\n\n - Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product\n\nWhat you'll bring:\n\n - 10+ years of experience in applied research, data science, or ML ","salary_min":220800,"salary_max":298800,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["search","embeddings","rag","healthcare","agents","generative-ai","nlp","llm"],"apply_url":"https://jobs.ashbyhq.com/drata/5fe5bc38-678d-468f-a762-a2144e88e45e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-26T15:23:45.786Z","expires_at":"2026-06-29T14:13:56.857373Z","created_at":"2026-05-27T14:14:32.846263Z","updated_at":"2026-05-30T14:13:56.969043Z","company_name":"Drata","company_slug":"drata","company_logo_url":"https://www.google.com/s2/favicons?domain=drata.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4ed2ca6e-f534-411e-b47e-bc955d32008f"},{"id":"80a16f64-3898-471c-b738-ec10c5b80e95","company_id":"fa25a1f6-acd0-42b6-a229-f4d258ed5c3d","title":"Staff Data Scientist","slug":"staff-data-scientist-b14f8c95","description":"Employee Applicant Privacy Notice \n Who we are: \n \n Shape a brighter financial future with us.\n Together with our members, we’re changing the way people think about and interact with personal finance.\n We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. \n Social Finance, LLC seeks Staff Data Scientist in San Francisco, CA: \n Job Duties: Identify high impact business opportunities to help members achieve their financial goals. Mentor and guide data scientists in the team by promoting best practices, strong technical decisions, coding standards, and thorough documentation. Develop and apply machine learning models to solve business problems. Evaluate and interpret the results of data analysis. Build strong relationships with stakeholders and present insights on a regular cadence communicating findings to both technical and nontechnical stakeholders. Design and implement data collection. Build data pipelines to deploy production level datasets. Collaborate with cross functional teams and business leader to understand needs and offer data driven solutions. Participate in internal team Knowledge sharing session and willingness to mentor junior Data Scientists in the team. Part time telecommuting is an option. Hybrid work from Sofi offices in San Francisco, CA. \n Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and three (3) years of experience in the job offered or related occupation.\n Special Skill Requirements: (1.) Artificial Intelligence (AI) \u0026 Machine Learning (ML); (2.) Natural Language Processing (NLP); (3.) Time Series Forecasting; (4.) ETL Pipelines; (5.) AWS (Sagemaker, S3, EMR); (6.) Advanced clustering; (7.) Data Visualization; (8.) A/B testing; (9.) Collaboration with cross-functional partners; (10.) Leadership. Any suitable combination of education, training and/or experience is acceptable. Part time telecommuting is an option. Hybrid work from Sofi offices in San Francisco, CA. \n Salary: $250,080.00 - $275,088.00 per year. \n Submit resume with references using the apply button on this posting or by email to: Req.# 1014.323.2 at: ATTN: HR, jobadverts@sofi.org .\n  \n  \n #LI-DNI\n Compensation and Benefits \n The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. \n  \n To view all of our comprehensive and competitive benefits, visit our  Benefits at SoFi   page!\n SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. \n The Company hires the best qualified candidate for the job, without regard to protected characteristics. \n Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. \n New York applicants: Notice of Employee Rights \n SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. \n Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time. \n Internal Employees \n If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.","salary_min":250080,"salary_max":275088,"location":"San Francisco, CA","workplace":"hybrid","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","nlp","cloud","data-science"],"apply_url":"https://sofi.com/careers/job/7741762003?gh_jid=7741762003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T16:28:47Z","expires_at":"2026-06-29T14:18:03.632869Z","created_at":"2026-05-27T14:18:55.187577Z","updated_at":"2026-05-30T14:18:03.744148Z","company_name":"SoFi","company_slug":"sofi","company_logo_url":"https://www.google.com/s2/favicons?domain=sofi.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/80a16f64-3898-471c-b738-ec10c5b80e95"},{"id":"eecb466b-db53-4f77-8014-1544cbb07fe9","company_id":"8108dfba-dc9f-4a18-b247-8cfbd20a0f26","title":"Senior Agent Architect","slug":"senior-agent-architect-ccdcc8ba","description":"About Parloa \n Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience — one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, Allianz, SAP, BarmeniaGothaer and TUI already deploying Parloa at scale.\n  \n About the Role: \n As a Senior Agent Architect at Parloa, you will play a key role in transforming customer service with AI Agents. In this customer-facing role, you will support the implementation of Parloa's solutions, enhancing customer experiences for clients and partners.\n Using your expertise in Large Language Models (LLMs), Prompt Engineering, NLP \u0026 NLU conversational design, and integration platforms, you will craft effective AI workflows and build connections to enterprise systems and ensure quality, performance, and end-to-end operational readiness.\n You will design, prototype, and validate conversational solutions for AI agent deployments, including the integration layer that connects Parloa's platform to customers' existing technology stacks, and guide customers and partners in maximising the value of Parloa's AI solutions.\n This is your opportunity to architect and deliver cutting-edge AI agent solutions while influencing how enterprise customer service evolves in the age of generative AI.\n  \n Areas of Ownership: \n \n Scope and implement AI Agent deployments, providing strategic advice and execution support to customers and partners. \n Leverage your knowledge of LLM internals (e.g., embeddings) to analyze customer requirements and design precise prompts for reliable, user-aligned behavior.\n Simplify complex workflows and processes into digestible conversational components, enabling LLMs to handle challenging tasks effectively. \n Fine-tune conversational flows and voice output (e.g., SSML, Lexicons, Regex) to align with customer brand standards. \n Build and configure integrations between customers' systems and Parloa's Platform, connecting external tools (e.g., CRMs, ERPs, ticketing systems, contact center platforms) via intergration platforms and APIs to deliver end-to-end enterprise solutions. \n Collaborate with Forward Deployed Engineers on complex or custom integration scenarios that go beyond standard integration capabilities. Identify and solve blockers together with other departments at Parloa (e.g. Product, Agent Integration Engineering, or Sales) and the customer. \n Apply structured testing approaches to validate AI agent behaviour, quality, and performance under real-world conditions. Document best practices, how-to guides, and product capabilities for internal and external audiences, representing the expertise of the Agent Architect team.\n \n  \n Who You Are: \n \n 3+ years of experience in enterprise customer-facing roles, with proven expertise in conversation design and AI agent development to create engaging and intuitive conversational experiences\n Ability to analyze customer requirements and craft LLM prompts that align with desired outcomes\n Entrepreneurial mindset with initiative, results orientation, and ability to identify opportunities for impact\n Proficiency with advanced prompting strategies such as chain-of-thought prompting, few-shot learning\n Strong project and stakeholder management skills, with passion for meeting milestones and effective communication\n Analytical and critical thinker with expertise in risk assessment, problem-solving, and strategy, plus solid knowledge of data structures, system integrations, and enterprise APIs\n Familiarity with API authentication patterns (OAuth, API keys, JWT), data transformation and field mapping logic\n Proficiency in REST API design, JSON/XML data structures, and API testing tools (Postman, etc.)\n Experience reading and consuming API documentation across enterprise SaaS platforms (CRMs, ERPs, contact center platforms)\n Exceptional attention to detail and logical thinking, with a proven ability to identify and address subtle nuances in conversational flows, ensuring a seamless and engaging user experience\n Familiarity with A/B testing methods to ensure AI agent performance at scale\n \n Nice to Have:\n \n Experience building custom connectors via integration platforms such as Paragon (TypeScript)\n Experience with Git-based version control and CI/CD pipelines\n Familiarity with middleware architecture\n \n  \n Our Recruiting Process: \n Talent Acquisition → Hiring Manager → Technical Interview(s) \u0026 Expert Interview → Bar Raiser\n  \n Why Parloa? \n We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments:","salary_min":113000,"salary_max":129000,"location":"New York, NY","workplace":"remote","job_type":"full-time","experience_level":"senior","tags":["llm","nlp","api-design","agents","generative-ai"],"apply_url":"https://job-boards.eu.greenhouse.io/parloa/jobs/4871790101","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-20T12:05:00Z","expires_at":"2026-06-29T14:19:33.573514Z","created_at":"2026-05-27T14:20:39.841537Z","updated_at":"2026-05-30T14:19:33.687292Z","company_name":"Parloa","company_slug":"parloa","company_logo_url":"https://www.google.com/s2/favicons?domain=parloa.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/eecb466b-db53-4f77-8014-1544cbb07fe9"},{"id":"c0abd638-4abc-4496-a03b-f8c15790103a","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Director of Safety ML","slug":"director-of-safety-ml-87e07a59","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 Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City \u0026 Chicago) our doors are open for you to come into the office as often as you'd like. \n We’re looking for a Director of Machine Learning to lead Reddit’s efforts in building industry-leading ML systems that keep our platform safe and foster healthy online communities. This leader will drive the strategy, development, and deployment of machine learning models that detect and prevent harmful content and behavior at scale.\n In this role, you will own the roadmap for Safety and moderation ML, lead a team of applied scientists and engineers, and partner cross-functionally across Product, Engineering, Safety operations, Trust \u0026 Community, and AI/ML Platform to innovate on real-time detection, automation, and user protection systems. You will leverage modern ML — including fine-tuned LLMs — to ensure Reddit remains a safe, welcoming, and positive environment for our global user base.\n Responsibilities \n \n Set the vision and strategy for applying ML to Trust \u0026 Safety, ensuring scalable, proactive protection against evolving abuse patterns.\n Lead and grow a high-performing Safety ML organization, including applied research, model development, productionization, and continuous improvement.\n Develop and deploy cutting-edge Safety ML systems (including fine-tuned LLMs and transformer models) that outperform state-of-the-art solutions in quality, latency, and efficiency.\n Partner with Trust \u0026 Safety, Product, Moderation, and AI/ML Platform teams to identify safety risks, emerging harm vectors, and ML opportunities that improve detection, enforcement, and user experience.\n Drive successful experimentation, evaluation, and model lifecycle management, ensuring high precision, recall, explainability, and policy alignment.\n Champion ethical and responsible AI practices in all Safety ML solutions.\n Track performance through metrics, research-based iteration, and alignment with Reddit’s safety policies and regulatory standards.\n Represent Safety ML leadership internally and externally — including conferences, publications, industry groups, and cross-company collaboration initiatives.\n \n Required Qualifications \n \n 10+ years of experience in Machine Learning, AI, or applied research, with a strong background in Trust \u0026 Safety, abuse prevention, detection, or content integrity.\n 5+ years of experience leading multi-disciplinary ML teams of 25+ team members (applied science, engineering, analytics) in a high-growth or high-impact environment. Must have experience managing people leaders (managers with direct reports)\n Proven track record of shipping ML systems at scale in production, ideally including transformer-based models and LLM fine-tuning.\n Depth in NLP, content understanding, detection systems, supervised and weak-supervision techniques.\n Strong cross-functional leadership skills, with ability to influence executives and foster alignment across Safety, Product, and Engineering.\n Thought leadership in responsible AI, safety ML research, or safety measurement frameworks.\n Entrepreneurial mindset — experience founding or scaling a product or ML org. \n \n Nice to Have \n \n Experience building or operating real-time abuse detection and automated moderation systems in a complex user-generated content ecosystem.\n Prior work in consumer-facing tech, social platforms, or large-scale community-driven products.\n \n Benefits: \n \n Comprehensive Healthcare Benefits and Income Replacement Programs\n 401k with Employer Match\n Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support\n Family Planning Support\n Gender-Affirming Care\n Mental Health \u0026 Coaching Benefits\n Flexible Vacation \u0026 Paid Volunteer Time Off\n Generous Paid Parental Leave \n \n  \n  \n #LI-SP1\n Pay Transparency: \n This job posting may span more than one career level.\n In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/c","salary_min":276700,"salary_max":387400,"location":"Remote (US)","workplace":"remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","nlp","llm","healthcare"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/7926627","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-15T17:09:23Z","expires_at":"2026-06-29T14:08:29.719274Z","created_at":"2026-05-16T14:09:00.966304Z","updated_at":"2026-05-30T14:08:29.833251Z","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/c0abd638-4abc-4496-a03b-f8c15790103a"},{"id":"4e2ca11a-e352-438c-98ba-172db0fbaedf","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"Research Engineer, Asta","slug":"research-engineer-asta-1852a645","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $118,800 - $178,200, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are: \n Are you passionate about AI and its potential to help accelerate science? \n Ai2's Asta Project ( https://allenai.org/asta ) aims to rapidly advance science, developing solutions in the areas of AI research assistants for scientists, literature understanding and synthesis, end-to-end discovery, human-AI interaction and intelligent interfaces, data-driven discovery, agents that can learn over time, methods for training agentic models, and the evaluation and benchmarking of agents. \n We are looking for a talented and motivated Research Engineer, ready to take on a complex challenge with huge potential impact for the future of AI, in particular, with skills and interest in the following focus areas :\n \n Automated and AI-assisted scientific discovery.\n Agentic planning, reasoning, learning, and evaluation.\n Data-driven discovery.\n Literature-driven ideation and discovery.\n Human-Agent Collaboration: Proactivity, Long-running agent, Memory, and context management.\n Continual learning, representation, and reasoning.\n Post-training, model tuning, distillation, and specialization.\n \n Who We Are:  \n The Asta Team (Semantic Scholar and Aristo, based in Seattle) at the Allen Institute for AI (Ai2) is an interdisciplinary research and engineering team focused on AI, ML, NLP, and HCI to support our mission of accelerating science with intelligent and interactive research assistants.  All of our scientific artifacts (data, model, software, papers) are open-sourced ( https://github.com/allenai ) and maintained. We regularly publish and present at high-profile journal/conferences in ML, NLP, HCI, and Accessibility.\n See links below for examples of our work. \n \n https://allenai.org/asta  \n https://allenai.org/blog/autodiscovery  \n https://allenai.org/papers \n \n Your Next Challenge: \n The essential functions include, but are not limited to, the following:\n \n Building infrastructure to facilitate the next generation of LLM and agentic research.\n Creating AI tools to facilitate scientific discovery in domains such as biology, cancer research, neuroscience, social science, etc.\n Designing, building, and training machine learning or language models for agentic workflows. \n Bridging the gap between cutting-edge research and a widely adopted product.\n Bringing software engineering best practices to a research environment.\n Supporting and collaborating with an open-source community.\n Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports.\n \n What You’ll Need: \n \n A bachelor’s degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP, or a related field, or equivalent relevant experience, and expertise in building ML infrastructure.\n 2+ years of experience building agentic infrastructure that handles tools, skills, and other artifacts. \n 2+ years of experience building infrastructure that handles data preprocessing/transformation and machine learning model training, evaluation, inference, and deployment.\n Knowledge of modern deep learning, natural language processing, and reinforcement learning techniques.\n Strong software engineering skills, particularly around building performant systems and debugging.\n Must have experience with Python and PyTorch/Jax/Tensorflow, agentic frameworks (e.g., MCP), as well as feel at ease in picking up new programming languages, libraries, or APIs as tools as project needs evolve.\n Familiarity with cloud compute resources (e.g., GCP, AWS, Modal) and containerization (e.g., Docker).\n Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives.\n \n Bonus qualifications:\n \n Advanced degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience.\n Contributions to open-source ML or research libraries (e.g., spaCy, AllenNLP, transformers, langchain).\n Experience successfully operating at scale in a production setting.\n Experience in HPC settings.\n Curiosity about AI research.\n \n Physical Demands and Work Environment: \n The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.\n \n Must be able to remain in a stationary position for long periods of","salary_min":118800,"salary_max":178200,"location":"Seattle, WA","workplace":"onsite","job_type":"full-time","experience_level":"junior","tags":["agents","healthcare","reinforcement-learning","pytorch","search","robotics","llm","nlp"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/7899565","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-13T20:50:09Z","expires_at":"2026-06-29T14:16:42.925464Z","created_at":"2026-05-14T14:17:46.499683Z","updated_at":"2026-05-30T14:16:43.039688Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4e2ca11a-e352-438c-98ba-172db0fbaedf"},{"id":"9c0d4b81-93bc-4563-b799-f97f18da3ba6","company_id":"e484db67-07a8-4412-8205-29832db55b17","title":"Senior Software Engineer, Search \u0026 Recommendations","slug":"senior-software-engineer-search-recommendations-756d9e55","description":"The Opportunity\n We're excited to welcome a talented and passionate Senior Software Engineer to join our highly skilled team. The ideal candidate will hold a deep comprehension of search and recommendations algorithms and infrastructure, including retrieval augmented generation (RAG), semantic search using embeddings, text indexing and retrieval, query understanding, various ranking algorithms etc.. In your crucial role, you'll be responsible for managing every aspect of our sophisticated enterprise search system, spearheading the design, development, and optimization of search system accuracy and performance.\n Your Impact\n \n Design, develop, and oversee our enterprise search infrastructure, employing a mix of vector databases, full-text search engine, and relational database techniques.\n Understand the user's information needs by developing deep learning-based NLP algorithms to analyze, reformulate and suggest search queries effectively.\n Design, implement, and deploy various ranking algorithms to deliver the most relevant results with the best user experience.\n Evaluate and optimize algorithm accuracy by focusing on key metrics..\n Constantly track and analyze end-to-end system performance, leading improvement initiatives as required.\n Stay informed about the latest industry developments and emerging technologies, aligning our search system with, or advancing it beyond, the industry benchmarks.\n \n We're looking for someone who\n \n Holds a Masters degree in Computer Science, or a relevant field, PhD a plus.\n 5+ years of experience in search, recommendation or question answering systems.\n In-depth knowledge of relevance measurement, tuning, and modeling.\n Engineering experience with large language models and RAG systems.\n Expertise in Python and/or C++.\n Exceptional problem-solving capabilities coupled with meticulous attention to detail.\n Outstanding communication skills to explain complex concepts convincingly to non-technical team members.\n Abilities to contribute individually while functioning effectively as part of a team.\n Familiarity with embedding-based search systems will be considered a major advantage.\n \n About Otter.ai \n We are in the business of shaping the future of work. Our mission is to make conversations more valuable.\n With over 1B meetings transcribed, Otter.ai is the world’s leading tool for meeting transcription, summarization, and collaboration. Using artificial intelligence, Otter generates real-time automated meeting notes, summaries, and other insights from in-person and virtual meetings - turning meetings into accessible, collaborative, and actionable data that can be shared across teams and organizations. The company is backed by early investors in Google, DeepMind, Zoom, and Tesla.\n Otter.ai is an equal opportunity employer. We proudly celebrate diversity and are committed to building an inclusive and accessible workplace.  We provide reasonable accommodations for qualified applicants throughout the hiring process. \n Accessibility \u0026 Accommodations  \n \n Otter.ai is committed to providing reasonable accommodations for candidates with disabilities in our hiring process.  If you need assistance or an accommodation during any stage of the recruitment process, please contact hr@otter.ai at least 3 business days before your interview. \n *Otter.ai does not accept unsolicited resumes from 3rd party recruitment agencies without a written agreement in place for permanent placements. Any resume or other candidate information submitted outside of established candidate submission guidelines (including through our website or via email to any Otter.ai employee) and without a written agreement otherwise will be deemed to be our sole property, and no fee will be paid should we hire the candidate. \n Salary range \n Salary Range: $185,000 to $230,000 USD per year \n This salary range represents the low and high end of the estimated salary range for this position. The actual base salary offered for the role is dependent based on several factors. Our base salary is just one component of our comprehensive total rewards package.","salary_min":185000,"salary_max":230000,"location":"Seattle, WA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["deep-learning","embeddings","nlp","llm","rag","search"],"apply_url":"https://otter.ai/careers?gh_jid=7732621003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-12T22:04:13Z","expires_at":"2026-06-29T14:13:42.254594Z","created_at":"2026-05-14T14:14:55.145461Z","updated_at":"2026-05-30T14:13:42.365676Z","company_name":"Otter.ai","company_slug":"otter-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=otter.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9c0d4b81-93bc-4563-b799-f97f18da3ba6"},{"id":"fab9d920-5bca-4369-9f94-ebd36718ac5e","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"Infrastructure Engineer ","slug":"infrastructure-engineer-54ff7957","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $100,080 - $150,120, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are: \n Are you a strong coder who loves automating systems so you only need to do anything just once? Are you motivated by the idea of working for a non-profit that’s working on AI for the common good?  If so, our infrastructure team is seeking an Infrastructure Engineer who thrives both independently and as part of a collaborative team. In this role, you’ll work closely with our IT  help desk team to identify opportunities for automation to keep our company running smoothly. If you enjoy taking initiative, learning on the fly, and making a real impact, we want you on our team.\n Who We Are:  \n At Ai2, you'll be joining a team of top AI researchers and talented engineers who are pushing the boundaries of what's possible. We have projects spanning natural language processing, robotics, artificial assistants, and fully open foundational models.  \n As an Infrastructure Engineer, you'll be a key part of our IT team, with a unique opportunity to build core infrastructure that supports all of our groundbreaking initiatives. If you join our team, you will help us invest in automated systems so we can continue to grow our impact while maintaining consistency across the company.\n We have a beautiful new office right across from Lake Union in Seattle; catered lunches five times a week; great pay and benefits; smart, friendly, and helpful coworkers; and even a couple of kayaks and paddleboards you can take out on sunny days.\n Your Next Challenge: \n The Infrastructure engineer will fill a critical role on the IT team, identifying and building pipelines that keep the whole company running smoothly.\n The essential functions include, but are not limited to, the following:\n Integrating software subscriptions with Okta for seamless user management \n \n Creating terraform configurations to for consistent management of GCP and AWS\n Building and deploying software that monitors for security vulnerabilities\n Investing in infrastructure to aggregate costs across all our services into a consistent format\n Deploying automation to audit user access across all of our software subscriptions\n Building and maintaining an automated pipeline for managing people, their accounts, and permissions\n \n Troubleshooting, documenting, and maintaining our internal systems \n \n Developing incident response automation, including auto-remediation workflows for common alerts\n Implementing backup and disaster recovery automation across critical systems and data stores\n \n What You’ll Need: \n \n Excellent communication, customer service, and problem-solving skills\n 5+ years of experience in IT or software development, with at least 3 years of experience focusing primarily on automation.\n Strong coding ability in a language such as Python\n Familiarity with using GitHub to organize code, and GitHub Actions for automation.\n Experience with specific IT automation tools, such as Terraform, Kandji/Iru, and Okta\n Experience administering and supporting major cloud providers such as AWS and Google Cloud\n Demonstrated knowledge of networking fundamentals\n Proven ability to collaborate with non-technical departments to translate business requirements into automated solutions\n Strong documentation experience with a focus on clear runbooks and end-user guides\n Familiarity with SAML and SCIM for identity and access management\n \n Bonus If You Have: \n \n A background in cybersecurity\n Hands on experience supporting security and compliance audits\n \n Physical Demands and Work Environment: \n The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.\n \n Must be able to remain in a stationary position for long periods of time. \n The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations. \n The ability to observe details at close range.\n Can work under deadlines.\n \n A Little More About Ai2: \n Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world’s biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.\n In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:\n \n We are a learning organization – because eve","salary_min":100080,"salary_max":150120,"location":"Seattle, WA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["security","healthcare","robotics","nlp","cloud","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/7902196","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-12T21:07:25Z","expires_at":"2026-06-29T14:16:42.679445Z","created_at":"2026-05-14T14:17:46.248785Z","updated_at":"2026-05-30T14:16:42.795036Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fab9d920-5bca-4369-9f94-ebd36718ac5e"},{"id":"06156a81-9587-4b11-9e8a-8eb784531cf2","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Machine Learning Engineer, LLM Evals \u0026 Observability","slug":"machine-learning-engineer-llm-evals-observability-2ace05f2","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n  \n About the Role: \n Building a great AI assistant is only half the battle – knowing whether it's actually great is the other half. Our team owns the measurement and quality layer that make Glean's Assistant and Agents reliably better over time: evaluation pipelines, quality eval-sets, LLM-powered judges, agent observability, and the tooling engineers use to understand what changed and why. It's a rare combination of infrastructure engineering, applied ML, and direct product impact. If you care deeply about quality and want to build the systems that make it measurable, this role is for you. \n You will:  \n \n Design and curate evaluation datasets – sampling strategies, query diversity, and golden sets that give reliable, representative coverage of real assistant behavior. \n Build and maintain large-scale evaluation pipelines that measure assistant quality across thousands of real user queries. \n Build LLM-powered judges that score metrics like correctness, completeness, and response quality, and align them against human judgment. \n Evaluate new models and product changes before they ship – providing the quality signal that gates launches and prevents regressions. \n Build observability infrastructure for AI agents: trace enrichment, data pipelines, and dashboards that make assistant behavior inspectable. \n Close the loop between quality measurement and improvement using eval results, customer feedback, and techniques like automated prompt iteration to help drive concrete gains in assistant behavior. \n Collaborate with engineers across the company to make evals a first-class part of how we ship. \n \n About you: \n \n 2+ years of software engineering experience with strong coding skills. \n Strong backend fundamentals in Go and Python; comfortable with distributed data pipelines. \n Experience working with LLM evaluation, reinforcement learning from human feedback, natural language processing, or other large systems involving machine learning. \n Analytically rigorous – you think carefully about what offline metrics actually predict about real user experience. \n Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company \n You care about quality – not just in the systems you build, but in the product you're helping measure and improve. \n \n Location:   \n \n This role is hybrid (3-4 days a week in one of our SF Bay Area offices) \n \n Compensation \u0026 Benefits: \n The standard base salary range for this position is $200,000 - $300,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. \n We offer a comprehensive benefits package including competitive compensation, Medical, Vis","salary_min":200000,"salary_max":300000,"location":"Mountain View, CA","workplace":"onsite","job_type":"full-time","experience_level":"junior","tags":["agents","llm","nlp","data-pipeline","reinforcement-learning","cloud","machine-learning","evaluation"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4694716005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-12T19:37:57Z","expires_at":"2026-06-29T14:03:13.819261Z","created_at":"2026-05-14T14:03:50.554084Z","updated_at":"2026-05-30T14:03:13.927219Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/06156a81-9587-4b11-9e8a-8eb784531cf2"},{"id":"09910d3a-20a6-4d06-b7f3-afd75e4589bc","company_id":"1a3abe34-d1c1-45b9-9259-3e2e007a961c","title":"Senior Research Scientist","slug":"senior-research-scientist-7d31e825","description":"About Voyage AI Team at MongoDB \n Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions.\n Position Overview \n We are seeking a Senior Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. \n Responsibilities \n \n Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers. \n Innovate in next-generation information retrieval and LLM agent paradigm.\n Collaborate closely with other research scientists and research engineers as well as peers across the organization.\n \n Qualifications \n \n PhD degree in Computer Science or related field\n Strong background in machine learning, deep learning, and natural language processing\n Familiarity with training distributed training of neural networks for language and visual understanding\n \n What We Offer \n \n Opportunity to work on real-world problems at the cutting edge of AI research\n Opportunity to utilize research vision to innovate the entire company and make real-world impact\n Exposure to the full lifecycle of AI model development, from research to production\n Our compensation (base + equity) for this position is competitive with frontier AI labs\n \n About MongoDB \n MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.\n With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.\n Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. \n To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world!\n MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.\n MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.\n Req ID: 2273430550\n MongoDB’s base salary range for this role is posted below. Compensation at the time of offer is unique to each candidate and based on a variety of factors such as skill set, experience, qualifications, and work location. Salary is one part of MongoDB’s total compensation and benefits package. Other benefits for eligible employees may include: equity, participation in the employee stock purchase program, flexible paid time off, 20 weeks fully-paid gender-neutral parental leave, fertility and adoption assistance, 401(k) plan, mental health counseling, access to transgender-inclusive health insurance coverage, and health benefits offerings. Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.\n MongoDB’s base salary range for this role in the U.S. is:\n $126,000 — $248,000 USD","salary_min":126000,"salary_max":248000,"location":"Palo Alto, CA","workplace":"onsite","job_type":"full-time","experience_level":"senior","tags":["search","computer-vision","embeddings","llm","nlp","distributed-systems","deep-learning","research"],"apply_url":"https://www.mongodb.com/careers/job/?gh_jid=7891161","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-11T14:01:23Z","expires_at":"2026-06-29T14:08:48.066799Z","created_at":"2026-05-11T14:10:36.176538Z","updated_at":"2026-05-30T14:08:48.181646Z","company_name":"MongoDB","company_slug":"mongodb","company_logo_url":"https://www.google.com/s2/favicons?domain=www.mongodb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/09910d3a-20a6-4d06-b7f3-afd75e4589bc"}],"page":1,"per_page":20,"total":362,"total_pages":19}