Jobs at Snorkel AI

Conduct foundational research on reinforcement learning and alignment for large language models. Develop preference datasets, reward models, verifiable rewards, and RL training pipelines using methods such as GRPO, RLHF, RLAIF, and DPO. Prototype scalable training recipes, collaborate with research and engineering teams, translate findings into customer-ready data products, and contribute to publications and internal knowledge sharing.

Own monthly, quarterly, and annual close processes; prepare and review journal entries, reconciliations, accruals, and audit support. Build commission and bonus models, manage project-based margin accounting, and oversee equity, debt, warrant, AP, expense, and spend accounting. Improve controls, documentation, automation, and ERP processes while mentoring accounting staff and partnering cross-functionally with Finance, Sales, People, Legal, Revenue, and Operations.

Leads development of frontier AI benchmarks and datasets in collaboration with academic and commercial partners. Designs evaluation datasets, translates research findings into customer-facing narratives, informs product and company strategy, and represents Snorkel through publications, talks, reports, and customer engagements. Requires expertise in AI/ML evaluation or NLP, rigorous experimental design, strong communication, cross-functional collaboration, and interest in AI data commercialization.

Own Snorkel AI’s $30M Open Benchmarks Grants program end to end, including application cycles, reviews, funding, milestones, public releases, partner relationships, portfolio budget, resource allocation, and impact measurement. Coordinate research, delivery, legal, finance, and marketing teams while building a scalable multi-year research program and supporting external AI research collaborators.

Owns supply operations for specialized expert domains, including staffing plans, capacity forecasting, expert allocation, bench management, and project matching. Partners with recruiting, delivery, expert experience, BPOs, and analytics to ensure projects are staffed efficiently. Tracks supply performance, resolves gaps, develops SOPs, and improves scalable operating processes.

Design and deploy generative AI and machine learning solutions for customers, spanning use-case scoping, data exploration, model development, evaluation, and deployment. Build RAG systems, fine-tuning pipelines, prompt engineering recipes, and agentic workflows. Lead customer relationships, stakeholder education, workshops, and strategic initiatives while translating recurring challenges into reusable tooling, workflows, and best practices. Collaborate with Solutions, Product, and Applied AI teams to guide roadmaps and deliver business value.

Own and evolve Snorkel AI’s brand identity across visual systems, guidelines, campaigns, websites, events, research content, and data visualizations. Build scalable Figma libraries and templates, direct agencies and freelancers, lead high-visibility launches, translate technical research into compelling visuals, and establish efficient design review and approval processes. The role requires strong independent judgment, senior stakeholder influence, and hands-on expertise in brand design, typography, layout, color, and composition.

Build and scale machine learning systems for frontier AI data generation and evaluation. Responsibilities include efficient agentic evaluations, model routing, fine-tuning and serving smaller open-weight models, predictive task-difficulty modeling, LLM-as-judge measurement, and productionizing research prototypes. The role requires rigorous experimentation, statistical analysis, strong Python and software engineering, and end-to-end ownership of production ML or software systems.

Advance AI data and agentic environment creation by designing scalable pipelines combining automated generation, real-world data, and expert judgment. Run experiments, evaluate data and model performance, collaborate with engineering, product, customers, and domain experts, and translate research prototypes into production workflows. The role also involves developing expert-authoring workflows, monitoring frontier research, and representing findings through publications, talks, blogs, and customer engagements.

Own Snorkel AI’s communications strategy across press, podcasts, awards, speaking opportunities, and media coverage. Develop compelling stories from research, benchmarks, customer results, and executive perspectives. Write pitches, bylines, releases, and supporting content while partnering with Research, Product Marketing, and Content teams. Build relationships with technology and business media, podcasts, and influencers, manage awards and conference submissions, and track communications performance.

Build infrastructure for large-scale AI and agentic workloads, including synthetic data generation, evaluation, orchestration, distributed compute, simulation environments, LLM routing, observability, and developer tooling. The role requires operating nondeterministic AI systems in production, improving reproducibility and reliability, and leading complex engineering initiatives across research, product, and engineering teams.

Build and deliver computer-use agent environments, datasets, evaluators, verifiers, and production solutions for AI labs and enterprise customers. Lead technical engagements from discovery through implementation and delivery, diagnose agent failures, run experiments, and improve reliability and performance. Partner with customers and internal engineering, research, and product teams while creating reusable frameworks, tooling, standards, and technical best practices. Provide technical leadership and communicate tradeoffs and recommendations to stakeholders.

The Senior Product Manager will lead development for AI data systems, ensuring product quality, improving workflows, and collaborating with cross-functional teams to deliver scalable solutions.

Maintain SOC 2 Type I and Type II compliance, coordinate audits and remediation, automate evidence collection through Vanta and Drata, manage access reviews and policy governance, support customer security questionnaires, and align controls with NIST, FedRAMP, and CMMC requirements. Partner with engineering and security teams on compliance-as-code, cloud controls, vendor risk management, metrics, incident evidence preservation, and federal readiness.

Build and maintain internal IT infrastructure as a product through automation, identity and access management, endpoint lifecycle management, networking, API integrations, workflow orchestration, internal tools, AI integrations, security scripting, alerting, and compliance automation. The role emphasizes Python or JavaScript development, Okta or Azure AD, MDM platforms, REST or GraphQL APIs, and security-first engineering practices.

Lead the Forward Deployed Engineering function, overseeing technical execution of data services and building a high-performing engineering team focused on AI data pipelines and workflows.

The Senior/Staff Research Scientist will develop and implement AI techniques, prototype solutions, and collaborate with teams to apply research in real-world settings.

Recruit Product talent for a high-growth AI startup by developing sourcing strategies, building diverse pipelines, analyzing recruiting metrics, delivering excellent candidate experiences, partnering with hiring managers, monitoring market trends, managing interview processes, and supporting onboarding and immigration. The role requires strong startup recruiting expertise, Product talent market knowledge, stakeholder coaching skills, and proficiency with modern recruiting tools.

Build and operate platform infrastructure, backend services, agent infrastructure, event-driven data pipelines, governance systems, CI/CD frameworks, and observability tooling. The role includes designing distributed systems on AWS, enforcing RBAC and compliance controls, optimizing infrastructure costs, defining reliability standards, participating in on-call, and leading complex engineering initiatives across teams.

Senior Technical Recruiter responsible for developing engineering recruiting strategies, sourcing passive candidates, managing pipelines, delivering excellent candidate experiences, partnering with engineering hiring managers, analyzing recruiting metrics, monitoring talent markets, coordinating interviews, improving hiring processes, and supporting onboarding and immigration. The role requires extensive full-cycle startup recruiting experience focused on software, AI/ML, and infrastructure engineering.