Snorkel AI FDE
Senior/Staff FDE - Synthetic Data Generation
- Location New York City, NY (Hybrid); San Francisco, CA (Hybrid)
- Posted 2026-08-27
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Skills
PythonEvalsAgents
Excerpt from the original posting
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Forward Deployed Engineer focused on Synthetic Data Generation to partner with leading AI labs and enterprises on their most critical AI initiatives. In this role, you will lead the technical execution of complex customer engagements where synthetic data is used to improve model training, evaluation, and performance. You will translate ambiguous model and data challenges into effective data strategies, build scalable generation and evaluation pipelines, and use experimentation to continuously improve data quality and downstream model outcomes. You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements. Main Responsibilities Synthetic Data Generation & Evaluation - Design and build scalable synthetic data generation, transformation, filtering, and evaluation pipelines for complex AI use cases - Translate model objectives, failure modes, and data gaps into synthetic data strategies, experiments, and technical specifications - Develop LLM- and ML-assisted workflows to generate high-quality training and evaluation datasets across targeted behaviors, domains, and edge cases - Build automated evaluators, quality checks, and measurement frameworks to assess correctness, relevance, diversity, coverage, and adherence to customer requirements - Design and run experiments to measure the impact of synthetic data on downstream model performance and iteratively improve generation approaches - Package and deliver production-grade datasets with standardized formats, quality assurance, and clear documentation Forward Deployed Engineering & Customer Partnership - Lead technical workstreams from initial solution design through production delivery, navig…