TL;DR

Head of Forward-Deployed Engineering (AI): Building and leading a forward-deployed engineering team to deliver high-quality datasets for critical AI initiatives with an accent on end-to-end data pipeline quality, ML approaches, and HITL techniques. Focus on scoping requirements for complex AI datasets, developing robust systems for task orchestration, and driving continuous improvement through reusable workflows.

Location: New York City, NY (Hybrid); Redwood City, CA (Hybrid); San Francisco, CA (Hybrid)

Salary: $220,000 - $330,000 USD

Company

Snorkel AI helps enterprises transform expert knowledge into specialized AI at scale, focusing on the data used to build AI systems.

What you will do

  • Build and lead the Forward Deployed Engineering DaaS organization, setting a clear vision 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 and data generation, quality estimation, and data-centric feedback loops that guide human input.
  • Partner with customers to scope requirements for complex, novel AI datasets and translate needs into delivery-ready workflows.
  • Develop robust systems for request intake, task orchestration, SLA tracking, and progress monitoring to ensure seamless execution and prevent critical delivery gaps.
  • 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.

Requirements

  • 10+ years of experience in applied data or ML engineering roles, including 5+ 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).

Nice to have

  • Experience working with data annotation workflows or internal tooling for data delivery orgs

Culture & Benefits

  • Join a company with market-proven solutions, robust funding, and rapid scaling.
  • Shape priorities and initiatives, influence key strategic decisions, and directly impact ongoing success.
  • Deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions.
  • Build your career in an environment designed for growth, learning, and shared success.