Snorkel AI is looking to build and lead a machine learning team within their Expert Data-as-a-Service organization to scale machine learning and data science excellence across delivery workflows.
Requirements
6+ years of experience in machine learning roles, with 2+ years in technical management positions
Proven track record of managing technical teams in fast-paced, delivery-focused environments with competing priorities
Experience as a player-coach—comfortable being hands-on while supporting and scaling a small team
Strong practical experience with LLM-based workflows, Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
Bonus: experience working with labeling workflows or internal tooling for data delivery orgs
Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
Responsibilities
Build and lead the Data Science and Engineering, Data-as-a-Service organization setting a clear vision and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
Own and evolve the ML components of the DaaS stack, including model-assisted labeling, quality estimation, and data-centric feedback loops that guide human input
Define and implement scalable processes for data generation and validation, quality measurement, and delivery-readiness across a range of annotation projects
Develop robust systems for request intake, task distribution, SLA tracking, and progress monitoring—ensuring critical delivery support doesn’t fall through the cracks
Prototype and deploy LLM-based workflows to assess annotation quality, augment human review and data generation, and accelerate delivery timelines
Collaborate cross-functionally with research and engineering teams to develop and productionize HITL data generation methods, quality techniques and improve internal delivery tooling
Drive continuous improvement by developing reusable workflows, surfacing operational insights, and helping the org scale faster with higher quality
Other
2+ years in technical management positions
Proven track record of managing technical teams in fast-paced, delivery-focused environments with competing priorities
Experience as a player-coach—comfortable being hands-on while supporting and scaling a small team
Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
Bachelor's degree or equivalent experience (not explicitly mentioned but implied)
