Snorkel AI

Software Engineer

• Design and implement centralized learning hubs and configure learning platforms, assessment, and certification systems.
• Create information architecture for discoverability, design end-to-end learning journeys, and build adaptive onboarding experiences and learning path architecture.
• Design and develop certification and badging programs with clear criteria and engaging UI.
• Establish a data infrastructure that connects enablement systems, create systems for tracking learner progress, and build dashboards for real-time visibility into learning effectiveness.
• Design gamification elements and recognition systems, create notification strategies and engagement triggers, and design A/B testing frameworks to optimize learning experiences.

Learning Experience Developer, Enablement

Learning and Development

• Develop comprehensive curricula and role-based training programs for Snorkel’s GTM, Delivery, Product Operations teams and our Expert Contributor network.
• Design and produce modular, self-paced multimedia content, including videos, screencasts, animations, and interactive learning modules, alongside practical job aids.
• Create realistic case studies and simulations from customer engagements, and write clear, concise instructional copy to support competency acquisition across teams.
• Storyboard learning experiences and strategically organize content for maximum discoverability and accessibility.
• Establish a systematic process for gathering feedback, analyzing usage data, and regularly updating training materials for continuous improvement and relevance.

Instructional Designer, Enablement

• Develop comprehensive curricula and role-based training programs
• Design and produce modular, self-paced multimedia content
• Create realistic case studies and simulations from customer engagements
• Establish a systematic process for gathering feedback and updating training materials

Instructional Designer – Enablement

Learning Experience Developer – Enablement

Product Manager

• Lead development across our agentic data systems, task-quality infrastructure, and data-acceleration initiatives.
• Work closely with Research, Engineering, Data Operations, and Design to define product vision, roadmap, and execution plans for intelligent workflow systems that optimize data pipelines, improve annotation/task quality, and enable faster and more efficient delivery of ML-ready data.

Staff Product Manager – AI/ML

• 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

Head of Forward-Deployed Engineering, DaaS

AI Engineer

• Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform.
• Develop and implement state of the art AI techniques such as retrieval-augmented generation (RAG), fine-tuning, prompt engineering, AI agents, ML model training, and optimizing model performance for real-world deployment to maximize business impact.
• Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow.
• Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.
• Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams
• Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
• Annual travel up to 25%.

Applied AI Engineer – Enterprise Solutions

• Develop and execute a strategic roadmap that aligns our teams to drive seamless product development that supports our business goals.
• Lead cross-functional collaboration between Engineering, Delivery, Sales, Marketing and our Expert Contributor network to deliver a cohesive and user-friendly platform for our internal and external customers.
• Foster a culture of fast iteration, learning from failures, and continuous improvement
• Advocate for research investments, understanding their impact and ensuring significant differentiation
• Provide technical and strategic product leadership while balancing short-term execution with long-term vision
• Partner with leadership and internal stakeholders to scale and evolve our DaaS platform

Director, Product Management – Data-as-a-Service

Attorney

• Serve as the company’s chief legal advisor, partnering with the executive team and Board on all legal and regulatory matters.
• Build and scale a high-performing legal organization that supports Snorkel AI’s rapid global growth.
• Develop the legal frameworks underpinning our Data-as-a-Service platform and two-sided data annotation marketplace.
• Oversee all customer, vendor, and partner contracts, with an emphasis on complex data licensing, SaaS, and platform agreements.
• Advise on product development and data governance to ensure compliance with evolving AI, data, and privacy laws globally.
• Manage corporate structure, equity, and governance matters in partnership with Finance and the Board.
• Support fundraising, M&A, and strategic transactions as a key deal architect.
• Drive IP strategy across software, data, and AI model assets.
• Protect and commercialize Snorkel AI’s proprietary technology and data partnerships.
• Partner with People and Finance to navigate employment law issues and global compliance obligations.
• Build scalable policies and frameworks to support our hybrid and distributed teams.
• Operate as a central node across teams — enabling business velocity while managing risk with clarity, pragmatism, and speed.
• Balance business enablement with legal rigor to ensure Snorkel AI continues to innovate responsibly.

VP of Legal

Operations

• Build and refine ticketing processes to streamline operations and improve response times
• Design and implement automated form processes that reduce manual work and improve data collection
• Create automated email workflows to enhance communication and operational efficiency
• Develop custom queries to extract actionable insights from operational data
• Leverage Zapier, Airtable, and other no-code/low-code tools to connect systems and automate workflows
• Design scalable data workflows that leverage internal tools, external vendors, and various pieces of automation
• Drive faster decision-making abilities for the team by exposing key insights from within the process
• Maximize marketplace efficiency and work with cross-functional partners to raise issues and implement corrective actions
• Partner with teams across the organization to identify operational bottlenecks and implement solutions
• Manage external partnerships and be a point of contact for them in resolving issues

Operations Manager – Supply

Research Scientist

• Design, implement, and validate novel AI techniques for data development such as synthetic data generation, utilizing techniques such as LLM as a Judge
• Prototype and build end-to-end workflows, integrating research ideas into scalable systems.
• Write high-quality, maintainable code, ensuring robust implementation of research-driven innovations.
• Move fast and adapt—iterating on solutions in response to new challenges, customer needs, and emerging research.
• Work closely with real-world design partners, testing solutions in applied settings with measurable impact.
• Collaborate with research scientists, engineers, and industry partners to push forward Snorkel AI’s broader research initiatives and rapidly productionize prototypes.

Senior/Staff Research Scientist

Program Manager

• Build and refine ticketing processes to streamline operations and improve response times
• Design and implement automated form processes that reduce manual work and improve data collection
• Create automated email workflows to enhance communication and operational efficiency
• Develop custom queries to extract actionable insights from operational data
• Leverage Zapier, Airtable, and other no-code/low-code tools to connect systems and automate workflows
• Design scalable data workflows that leverage internal tools, external vendors, and various pieces of automation
• Drive faster decision-making abilities for the team by exposing key insights from within the process
• Determine user information that is missing, which leads to user experience improvements
• Maximize marketplace efficiency and work with cross-functional partners to raise issues and implement corrective actions
• Grow our user base through implementation of retention and incentivization programs
• Partner with teams across the organization to identify operational bottlenecks and implement solutions
• Manage external partnerships and be a point of contact for them in resolving issues

Operations Program Manager

Data Scientist

• 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
• 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
• 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
• 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

Data Scientist – Data-as-a-Service

Growth Marketing

• Own the Contributor Funnel: Define and manage the full journey—from initial acquisition through conversion, onboarding, engagement, and retention.
• Set the Right Metrics: Establish KPIs and dashboards that measure contributor conversion, funnel health, quality, and satisfaction. Use data to prioritize initiatives and track progress.
• Identify & Solve Gaps: Diagnose bottlenecks or friction points in the contributor experience; lead cross-functional efforts with Ops, Product, Growth, and external stakeholders to resolve them.
• Develop Strategy for Network Growth: Design and execute strategies to grow our contributor base sustainably, balancing demand for expertise with supply availability.
• Build Contributor Programs: Launch and scale initiatives (training, enablement, recognition, community) that improve contributor satisfaction, retention, and performance.
• Be a Voice for Contributors: Serve as the advocate for contributor needs internally, shaping product, process, and tooling decisions.
• Drive Cross-Functional Alignment: Collaborate with GTM, Delivery, Ops, and Analytics teams to ensure contributor supply supports overall business growth.

Senior Manager, Growth – Expert Contributor Experience

• Lead and develop the Production Manager team
• Drive operational excellence by overseeing project planning
• Collaborate with research, engineering, GTM, and operations stakeholders
• Identify and implement improvements to workflows
• Translate customer needs into actionable delivery plans

Manager, Delivery Operations

Product Operations

• Act as the bridge between Product, Engineering, and customer-facing teams, ensuring user needs and product priorities stay in sync.
• Lead product program management—driving planning, launch, and rollout of new features with strong alignment between customers, contributors, and product.
• Partner with Enablement to equip Technical Delivery Managers, Production Managers, Sales, and Expert Contributors with the tools and training to adopt and succeed with Snorkel’s products.
• Build and manage a Voice of the Customer program, consolidating feedback across all channels and surfacing insights to inform roadmap and R&D investment decisions.
• Serve as a strategic advisor to Product leadership, influencing roadmap prioritization and long-term product strategy with data-driven insights and customer context.

Product Operations Lead

Manager

• Provide oversight on complex customer projects
• Ensure delivery is on-time, on-budget, and meets quality standards
• Recruit, mentor, and develop a group of technical delivery managers
• Establish best practices, playbooks, and scalable processes
• Collaborate closely with the Head of Delivery
• Work with research, engineering, product, and client-facing teams
• Identify opportunities to innovate and streamline delivery methodologies
• Support TDMs in interfacing with clients

Technical Delivery Manager

• Found the Analytics Function: Build the strategy, processes, and tools for analytics within the DaaS org, creating the foundation for a function that will scale with the business.
• Own Capacity & Supply Modeling: Develop and maintain models that balance demand for expert contributors with available supply, helping drive forecasting, staffing, and resource allocation.
• Drive Data Infrastructure & BI: Partner with Ops, Eng, and Product to establish reliable pipelines and dashboards to monitor data health, contributor quality, and operational metrics.
• Analyze & Optimize Contributor Experience: Own the measurement framework for the expert contributor journey—including conversion funnels, retention, and quality metrics—to surface opportunities for growth and efficiency.
• Guide Business Decision-Making: Partner with the GM and DaaS leadership to provide actionable insights on GTM, delivery operations, and supply/growth trade-offs.
• Scale the Team: Over time, recruit, mentor, and lead a team of analysts and data scientists as new needs are identified, defining the culture and operating model of Analytics at Snorkel.

Senior Analytics Lead – Data-as-a-Service

Producer

• Collaborate with Technical Delivery Managers to meet project timelines, deliverables, and quality standards
• Engage with Expert Contributors to ensure high-quality datasets are delivered to customers
• Conduct quality reviews to maintain data annotation accuracy and consistency
• Monitor pipeline health and implement proactive solutions to prevent bottlenecks
• Track project progress and performance through data analysis and reporting
• Develop documentation for labeling guidelines and operational processes
• Partner with stakeholders across teams to resolve blockers and sustain production efficiency
• Provide regular updates to stakeholders on progress and key insights

Production Manager

Technical Project Manager

• Lead data development projects from start to finish, owning every phase of the project lifecycle
• Coordinate cross-functional teams and provide spirited encouragement to drive cross-functional ownership
• Manage risks: maintain a risk management plan and apply mitigation strategies as needed
• Keep initiatives on track and on budget; manage project finances by tracking expenses and aligning resources
• Break tasks down, track progress, and keep stakeholders informed about changes, risks, or blockers (Make Work Visible)
• Convert abstract requirements into clear project plans (Bridge Concept and Execution)
• Oversee data ingestion, transformation, and storage across multiple systems, leveraging SQL, JSON, and query management (Manage Data Flows)
• Collaborate with the Client Success team to structure project details for external or client-facing materials
• Present updates and forecasts using data-driven insights for diverse audiences (Communicate with Data)