Research Scientist - Human-AI Systems
Snorkel AI · San Francisco, CA (Hybrid)
About this role
**About Snorkel** At Snorkel, we believe meaningful AI doesn’t start with the model—it starts with the data. We help enterprises transform expert knowledge into specialized AI at scale, enabling teams to build custom AI with their data faster than ever. **Role: Research Scientist — Human-AI Systems** We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input—scaling these pipelines to target frontier model performance gaps and expand data and environment diversity. **Main Responsibilities** - Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation. - Design and run rigorous experiments to validate proof-of-concepts, measure impact on data quality, pipeline efficiency, and model performance, and communicate findings. - Partner with engineering, data operations, domain experts, and customers to turn research prototypes into reliable production workflows. - Work directly with domain experts to design and test workflows that help them author, review, and refine data and environments. - Cross-functionally surface research findings that inform the company roadmap. - Stay at the frontier of research in data and agentic environment creation and bring best practices into Snorkel’s workflows. - Represent Snorkel’s research externally through publications, blog posts, conference talks, and customer engagements. **Preferred Qualifications** - Strong research background in AI, machine learning, NLP, LLMs, or related fields; experience developing and evaluating new methods. - Experience building environments for AI agents (e.g., automated research, computer use, coding, or professional domain workflows). - Experience with one or more of: synthetic data generation, human-in-the-loop workflows, reinforcement learning, agent environments, or model evaluation. - Strong experimental design skills (e.g., defining hypotheses and conducting ablations). - Familiarity with software engineering best practices (clean coding, modular design, version control). - Ability to collaborate with domain experts and translate knowledge into concrete tasks, evaluation criteria, and repeatable workflows. - Comfort with rapid iteration, ambiguous research questions, and moving ideas from experimentation into production. - Ph.D. in machine learning, NLP, or related field preferred (equivalent industry/research lab experience considered). **Location** San Francisco, New York, **OR REMOTE** **Compensation** $200,000 — $375,000 USD (actual compensation determined by skills, qualifications, experience, and geographic location) **Equal Opportunity** Snorkel AI is an Equal Employment Opportunity employer committed to building a diverse team. Reasonable accommodations are available for individuals with disabilities during the application/interview process—please contact to request accommodation.
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