Snorkel AI FDE
Senior/Staff Forward Deployed Engineer - Data as a Service
- Location New York City, NY (Hybrid); San Francisco, CA (Hybrid)
- Seniority staff
- Posted 2025-10-24
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role details
Builds and deploys data pipelines, develops quality measurement systems, and generates synthetic datasets to meet client expectations.
Summary generated by AI from the original posting.
Hard requirements to check first
- Clearance：not mentioned in the posting
- Work auth：not mentioned in the posting
Skills
PythonSQLEvalsdata sciencedata engineeringAI engineeringoperationsML-assisted workflowsevaluation workflowsquality standardsmeasurement frameworks
Excerpt from the original posting
About Snorkel 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! About the Role - Multiple Levels This is an engineering delivery role where you’ll translate ambiguous customer needs into production-grade data, evaluation, and ML-assisted workflows. This is a high-impact role focused on end-to-end ownership of the AI data pipeline lifecycle, including developing and deploying ML-based workflows and building the technical foundations that make our human-in-the-loop (HITL) data generation and review faster, more reliable, and more effective. You’ll work at the critical intersection of data science, data engineering, AI engineering and operations, partnering closely with our DaaS Delivery Operations team and cross-functional stakeholders. You’ll develop technical specifications, design evaluation workflows, implement quality standards, measurement frameworks, and ML-assisted applications which improve our data pipelines and unblock projects through technical innovation. This role is ideal for someone who is comfortable working throughout the delivery lifecycle, rolling up their sleeves to solve complex multi-faceted problems, thrives as a technical communicator and works well as a key member of a team. Main Responsibilities Project Execution & Delivery - Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations - Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and augment training data - Package and deliver production-grade datasets with standardized formatting, comprehensive documentation, and quality assurance - Configure and build custom appli…