Data Scientist - Data-as-a-Service

About the Role

Snorkel AI is hiring data scientists and engineers who will work directly on Snorkel projects,  partnering with leading labs and enterprises to design, develop, and deliver high quality AI/ML data products for their most critical AI initiatives. This is a high-impact, customer-facing role focused on end-to-end ownership of the AI data pipeline lifecycle. This includes developing and deploying ML-based workflows, and building the technical foundations that make our human-in-the-loop (HITL) data generation and review faster and more effective. 

You’ll work at the critical intersection of data science, data engineering, AI engineering and operations, partnering closely with our DaaS Delivery Operations team and cross-functional stakeholders. You’ll develop technical specifications, design evaluation workflows, implement quality standards, measurement frameworks, and ML-assisted applications which improve our data pipelines and unblock projects through technical innovation.

This role is ideal for someone who is comfortable working throughout the entire presales to delivery lifecycle, rolling up their sleeves to solve complex multi-faceted problems, thrives as a technical communicator and works well as a key member of a team.

Main Responsibilities

Pre-Sales & Discovery

• Partner with the Sales Team on client discovery calls to provide technical depth, assess solution fit, and scope Data-as-a-Service opportunities
• Develop and present tailored technical assets including specifications, data dictionaries, sample datasets, and client-specific demonstrations to illustrate feasibility and value
• Define project scope and success criteria in collaboration with customer stakeholders and internal delivery teams, ensuring alignment on technical requirements and capacity
• Design and execute calibration processes including baseline batches, benchmark reports, and evaluation frameworks that establish measurable project success metrics

Project Execution & Delivery

• Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations
• Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and augment training data
• Package and deliver production-grade datasets with standardized formatting, comprehensive documentation, and quality assurance
• Configure and build custom applications and off-platform solutions for non-standard or specialized client requirements

Production & Technical Partnership

• Define production specifications and workflows, securing technical alignment with client teams to enable seamless go-live transitions
• Provide ongoing technical support to Delivery Managers, addressing complex questions, resolving technical blockers, and supporting customer rebuttals
• Maintain specification consistency and alignment across customer and internal teams throughout the engagement lifecycle
• Identify and document workflow best practices and automation opportunities, collaborating with DaaS Engineering to continuously improve delivery capabilities

Technical Leadership & Innovation

• Maintain solution leaderboards and execute custom model benchmarking on existing datasets to demonstrate technical capabilities
• Drive continuous improvement of technical assets, evaluation frameworks, and delivery processes to enhance speed, quality, and scalability
• Support account growth by identifying upsell and cross-sell opportunities based on technical interactions with client engineering and research teams

What We’re Looking For

• 2+ years of experience in data science and engineering roles. Strong practical experience with Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
• Familiarity with LLM-based workflows and applying ML techniques in production contexts
• Experience leveraging Backend APIs and interpreting associated technical documentation

Please Note: Current U.S. work authorization required; this role does not offer visa sponsorship. Ideally, the candidate would be able to start as soon as possible (within 30 days).

Depending on your work location, the target annual salary for this position can range. Compensation include equity in the form of stock options. Snorkel also includes benefits (including medical, dental, vision and 401(k)).

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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