Head of Forward-Deployed Engineering
Quick Summary
About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.
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 between 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
~1 min readIn this role, you will build and lead our forward-deployed engineering (FDE) team, working directly with leading labs and enterprises to scope, build and deliver high quality datasets to support their most critical AI initiatives.
Sitting at the critical intersection of data engineering, ML engineering, operations, and customer engagement— leading scoping and preselling efforts. You'll also partner closely with the Snorkel delivery 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.
Responsibilities
~1 min read- →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 and data generation, 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
- →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
- →Drive continuous improvement by developing reusable workflows, surfacing operational insights, and enabling the organization to scale faster while maintaining high quality
- 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)
- Bonus: experience working with data annotation workflows or internal tooling for data delivery orgs
What We Offer
~1 min readAt 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.
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Listing Details
- Posted
- April 8, 2026
- First seen
- March 26, 2026
- Last seen
- April 19, 2026
Posting Health
- Days active
- 24
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- April 19, 2026
Signal breakdown
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