Head of Data Science, Snorkel AI
Data-as-a-Service
$240-300k
All offers include equity compensation in the form of employee stock options. Salary applicable to SF candidates & may differ for other locations
Data-centric enterprise AI platform for
Be an early applicant
Data-centric enterprise AI platform for
101-200 employees
Be an early applicant
$240-300k
All offers include equity compensation in the form of employee stock options. Salary applicable to SF candidates & may differ for other locations
101-200 employees
Company mission
To empower everyone to solve their most impactful problems through data-centric AI.
Role
Who you are
- 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
What the job involves
- Snorkel AI is hiring a hands-on technical leader to build and lead the machine learning team within our Expert Data-as-a-Service organization
- This is a foundational leadership role focused on scaling machine learning and data science excellence across our delivery workflows
- You’ll be responsible for hiring and mentoring a high-performing team, 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 machine learning and operations, you’ll partner closely with the 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
- Build and lead the Data Science and Engineering, Data-as-a-Service organization setting a clear vision and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
- Own and evolve the ML 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
Our take
Demand for AI is increasing in almost every industry, but the machine learning that fuels it is tedious to set up. In order to train machine learning algorithms, training data must be labelled manually, and this contributes to expenses in time, money and resources when integrating AI within a business.
Snorkel AI develops programmatic approaches to data labelling in order to automate the setup process of machine learning and decrease the required timeframe for a business to begin providing AI services. In addition to these automated data categorization services, the company also integrates data training, management, and analysis into a unified AI-deployment platform.
The complex computer science behind AI setup has resulted in many businesses without computer science backgrounds being left behind, and Snorkel AI has set this as their target audience. As of 2023, this customer base has tripled in size since Snorkel AI's founding and in 2024, enjoyed a new round of funding. With these promising developments, the company continues to innovate the sector.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 4 rounds)
May 2025
$100m
SERIES D
Aug 2021
$85m
SERIES C
Total funding: $235m
Company benefits
- Home office allowance
- Yearly wellness stipend
- Healthy meals, snacks & drinks in office
- 401k with a 100% match up to 5% of annual salary
- Regular team events
- Generous paid parental leave
- Work from home opportunities
- Health insurance
Company HQ
Centennial, Redwood City, CA
Leadership
Alex Ratner
(Co-founder & CEO)Studied at Harvard and received a PhD from Stanford. They are also an Assistant Professor at the University of Washington.
Paroma Varma
(Co-founder)They hold a PhD from Stanford and was VP of Corporate Relations at the Society of Women Engineers. They have collaborated with teams at Facebook and Intel.
Braden Hancock
(Co-founder & Head of Technology)They have a PhD in Computer Science from Stanford, and worked as a Research Assistant with the Air Force and MIT. They were also a Software Engineer at Google, and a Researcher at Facebook.
Henry Ehrenberg
(Co-Founder)They studied at Yale and Stanford and worked at Facebook as a Quantitative Engineering Intern and a Senior Applied Research Scientist.
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job
View 9 more jobs at Snorkel AI