Senior/Staff FDE - Synthetic Data Generation

At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.

We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

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.

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, navigating ambiguity and making sound technical decisions

• Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value

• Rapidly prototype and productionize solutions across models, data pipelines, APIs, and custom applications

• Communicate technical tradeoffs, experimental results, and recommendations clearly to technical and cross-functional stakeholders

• Serve as a trusted technical partner to customers and internal delivery teams, resolving complex blockers and driving alignment

Technical Leadership & Scale

• Identify recurring patterns across customer engagements and turn successful solutions into reusable pipelines, evaluators, tooling, and best practices

• Define and improve technical standards for synthetic data generation, experimentation, evaluation, and delivery

• Partner with DaaS Engineering and Product teams to