Research Scientist - Human-AI Systems
Snorkel AI· 316 - Research
Hybrid (New York City, NY; San Francisco, CA; Remote)$200k - $375kfull-timePosted 3w ago
About the role
Research Scientist focused on creating high-quality data and environments for AI agents by building and optimizing scalable pipelines that combine real-world data, automated generation, and human input. Works with domain experts, partners, customers, and product/engineering to reduce frontier model gaps and increase data/environment diversity. Hybrid/remote-friendly with locations in NYC, SF, or remote.
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-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communicate findings.
- Partner with engineering, data operation, 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.
- Work cross-functionally with data operations, product, and engineering to 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 that advance the conversation around data-centric AI.
Qualifications
- Strong research background in AI, machine learning, NLP, LLMs, or related fields, with experience developing and evaluating new methods.
- Experience building environments for AI agents in automated research, computer use, coding, or professional domain workflows.
- Experience with synthetic data generation, human in the loop workflows, reinforcement learning, agent environments, or model evaluation.
- Strong experimental design skills, including defining hypotheses and conducting ablations.
- Experience with software engineering best practices (e.g., clean coding, modular design, version control).
- Ability to collaborate with domain experts and translate their 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 a related field preferred; equivalent industry or research lab experience considered.
Skills
Required:Research in AI / ML / NLPExperiment designEnvironment/Agent workflow developmentCross-functional collaboration with domain experts
Nice to have:Synthetic data / human-in-the-loop / RL / agent environmentsSoftware engineering best practices
Last updated Oct 7, 2026. Interested? Apply on the company site.
About Snorkel AI
Shaping how AI learns through better data
Snorkel AI delivers the highest quality specialized datasets for frontier LLMs and enterprise models.
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