Snorkel AI - Research Scientist - Human-AI Systems

New York City, NY (Hybrid); San Francisco, CA (Hybrid); United States (Remote) - Hybrid$200k - $200k3w ago

In Office NA Artificial Intelligence Research Scientist Data Quality

Requirements

• 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 one or more of 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. • Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.

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.