Head of Data Science & Engineering, Data-as-a-Service

About the Role

Snorkel AI is hiring a hands-on technical leader to build and lead the data science and engineering team within our Expert Data-as-a-Service (DaaS) organization. This is a foundational leadership role focused on scaling data science excellence across our delivery workflows. You’ll be responsible for hiring and mentoring a high-performing team of data scientists and engineers, establishing best practices for data quality and validation, designing novel ML approaches to make human-in-the-loop techniques to make data generation and review more efficient. You will build the systems and tools that enable consistent, scalable, and high-quality data delivery to our customers.

Sitting at the critical intersection of data science, engineering and operations, you’ll partner closely with the DaaS Delivery Operations team and cross-functional stakeholders to define quality standards, develop measurement frameworks, drive ML-based workflows to improve data pipelines and unblock projects through technical innovation. As the founding member, you’ll also roll up your sleeves to define and own the workflows and processes that are needed to deliver exceptional data at scale.

Main Responsibilities

• Build and lead the Data Science and Engineering, DaaS organization setting a clear vision and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
• Own and evolve the data pipeline 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

What We’re Looking For

• 6+ years of experience in data science and engineering 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
• Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
• 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

Why Join Snorkel AI?

At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to found a function and have a broad, lasting impact across the company.

The salary range for this position based in the San Francisco Bay Area is $240,000 - $300,000. All offers include equity compensation in the form of employee stock options.

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