Hybrid Head of Forward-Deployed Engineering, DaaS

at Snorkel AI

• Job title: Head of Forward-Deployed Engineering, DaaS
• Job type: Full Time
• Experience level: Lead
• Salary: $220,000 - $350,000 per year
• Degree requirement: No Education Requirement
• Tech skills: Pandas, Python, SQL
• Location requirements: Hybrid, New York City, United States

About the role

• Head of Forward-Deployed Engineering leading teams at Snorkel AI. Focusing on data delivery and ML workflows in hybrid work setting.

Responsibilities

• Build and lead the Forward Deployed Engineering DaaS organization, setting a clear vision, defining the operating model and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
• Build, mentor, and motivate high performing teams, including cultivating skills and culture needed to consistently deliver exceptional outcomes and transformative impact.
• 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
• Partner with customers - including research and engineering teams at Frontier AI Labs - to scope requirements for complex, novel AI datasets and translate needs into delivery-ready workflows
• Establish and execute 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 orchestration, SLA tracking, and progress monitoring to ensure seamless execution and prevent critical delivery gaps
• 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 innovate, develop, and productionize HITL data generation methods, advanced quality techniques, and improve internal delivery tooling
• Drive continuous improvement by developing reusable workflows, surfacing operational insights, and enabling the organization to scale faster while maintaining high quality

Requirements

• 7+ years of experience in applied data or ML engineering roles, including 2+ years leading high-performing technical teams in hands-on management capacity
• Demonstrated success in customer facing roles, with a strong enthusiasm for data pipelines and LLM-based workflows.
• Proven track record of managing technical field teams in fast-paced, delivery-focused environments with competing priorities
• Experience as a player-coach—comfortable being hands-on while supporting and scaling the 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

Benefits

• All offers also include equity in the form of employee stock options