Research Scientist - Human-AI Systems
$200k - $375k • Remote • New York City, NY (Hybrid); San Francisco, CA (Hybrid); United States (Remote)
Posted 11d ago
Job Location
New York City, NY (Hybrid); San Francisco, CA (Hybrid); United States (Remote)
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
Snorkel AI is seeking a Research Scientist to advance the creation of high-quality data and environments for AI agents. You will build and optimize pipelines that integrate real-world data, automated generation, and human expert input. Collaborating with domain experts, academic partners, customers, and internal teams, you will scale these pipelines to address frontier model performance gaps and enhance data and environment diversity. Your work will empower human knowledge and judgment, enabling experts to refine data and agentic environments, solidifying Snorkel's position as a leader in frontier data solutions. This role is perfect for individuals passionate about advancing frontier AI through data and environment creation, and who enjoy translating research into scalable, reusable systems.
Responsibilities
- Design, implement, and optimize reusable pipelines combining AI capabilities with expert judgment for accelerated data and agentic environment creation.
- Design and conduct 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 operations, domain experts, and customers to transition research prototypes into reliable production workflows.
- Collaborate with domain experts to design and test workflows for authoring, reviewing, and refining data and environments.
- Work cross-functionally with data operations, product, and engineering to inform the company roadmap with research findings.
- Stay current with research in data and agentic environment creation and integrate best practices into Snorkel's workflows.
- Represent Snorkel's research externally through publications, blog posts, conference talks, and customer engagements.
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 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.
Benefits
- Meaningful opportunities to shape priorities and initiatives.
- Influence key strategic decisions.
- Directly impact ongoing success.
- Support for deepening technical expertise.
- Support for exploring leadership opportunities.
- Support for learning new skills across multiple functions.
- Environment designed for growth, learning, and shared success.