About Snorkel
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!
In this role, you will build and lead our forward-deployed engineering (FDE) team, working directly with leading labs and enterprises to design, build and deliver high quality datasets to support their most critical AI initiatives.
You’ll be responsible for establishing engineering best practices for data quality and validation. This includes designing innovative ML approaches to enhance human-in-the-loop (HITL) techniques and improving the efficiency of data generation and review processes. Your team will own systems and tools that enable consistent, scalable, and high-quality data delivery to our customers.
Sitting at the critical intersection of data engineering, ML engineering, and operations, you’ll partner closely with the DaaS 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.
Main 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
- 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
Compensation range for Tier 1 locations of San Francisco Bay Area and New York City, $220K - $350K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
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 own technical data workflows and be a founding member of the technical DaaS team.
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Be Your Best at Snorkel
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.
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What We Do
Our mission is to empower everyone to solve their most impactful problems through data-centric AI. To do this, we have introduced Snorkel Flow, a data-centric AI platform, and are building an incredibly talented team. We empower Fortune 500 enterprises such as Chubb and BNY Mellon, and several government agencies to accelerate AI application development by 10-100x.
Why Work With Us
The founding team spent over half a decade researching programmatic labeling, weak supervision, and other techniques to break through one of the biggest bottlenecks in AI: the lack of labeled training data. This research has resulted in Snorkel research project and 60+ peer-reviewed publications. Snorkel has developed and deployed its technology
