Job Description:
• Design, implement, and optimize reusable pipelines combining AI capabilities with expert judgment for data and agentic environment creation
• Design and run experiments to validate proof-of-concept approaches and measure effects on data quality, pipeline efficiency, and model performance
• Communicate research findings
• Partner with engineering, data operations, domain experts, and customers to turn research prototypes into reliable production workflows
• Design and test workflows with domain experts for authoring, reviewing, and refining data and environments
• Work cross-functionally with data operations, product, and engineering to inform the company roadmap
• Stay current with research in data and agentic environment creation and apply best practices
• Represent Snorkel's research 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, including clean coding, modular design, and 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
• Opportunity to influence key strategic decisions and directly impact company success
• Support for deepening technical expertise
• Leadership opportunities
• Opportunities to learn new skills across multiple functions
• Career growth, learning, and shared success
• Reasonable accommodation for individuals with disabilities
• Equal employment opportunities and benefits and privileges of employment