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.

Build and improve backend product capabilities for data cataloging, agent benchmarking, and workflow automation. Own features from user problem definition through design, implementation, launch, and production support. Develop APIs, services, data models, and workflow systems; investigate performance and production issues; contribute to architecture and code quality; and collaborate with Product, Design, and Engineering. The role is hybrid, requiring at least three days weekly in San Francisco or New York City.

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.

Lead a software engineering team building and operating Snorkel AI’s platform in government and regulated cloud environments. Define architecture, deploy services, establish infrastructure-as-code and CI/CD workflows, and ensure security, monitoring, vulnerability management, incident response, compliance, and auditability. Partner with platform, security, compliance, product, and applied AI teams while hiring, coaching, and developing engineers and setting technical standards.

Own headcount and operating expense planning, annual budgets, rolling forecasts, personnel cost models, variance analysis, procurement workflows, and spend management. Partner with department leaders, Accounting, People, Recruiting, Legal, and IT to guide hiring and investment decisions. Administer Ramp and planning systems, improve financial data integrations, and support consolidated reporting, executive reviews, and board materials.

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.

Leads Snorkel AI’s data partnership supply function, including sourcing proprietary data, building the supplier pipeline, negotiating licensing and commercial agreements, and managing partnerships through activation, sales, and renewal. Establishes qualification standards, pricing frameworks, operating metrics, and team capabilities while advising leadership on the AI data market and partnership strategy.

Leads Snorkel AI’s expert supply growth function, developing acquisition strategy, channel mix, partnerships, referral programs, BPO relationships, funnel optimization, analytics, and operating systems. Owns targets for acquiring, activating, and retaining specialized experts across domains and geographies. Builds and manages a high-performing team while partnering cross-functionally to improve quality, speed, cost, and marketplace capacity.

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.

Drafts, reviews, and negotiates customer, vendor, and other commercial agreements. Partners with business teams, manages high-volume contract workflows, improves templates and playbooks, and supports contract lifecycle processes and legal projects. The role requires strong commercial judgment, communication, negotiation skills, and the ability to balance legal risk with business objectives in a fast-growing technology company.

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.

Own Snorkel’s Agentic Data and Reinforcement Learning Environments product roadmap. Define data product strategy, shape new product areas, and collaborate with research, academic partners, go-to-market, and operations teams. The role requires deep AI/ML and LLM post-training knowledge, experience building data products and technical roadmaps, customer discovery with technical buyers, quantitative market and unit-economic analysis, and strong influence across research-oriented stakeholders.

Leads Snorkel AI’s GTM systems strategy, Salesforce architecture, data governance, automation, and AI transformation. Manages a technical systems team, owns the GTM technology roadmap and vendor relationships, improves lead-to-cash processes, and partners across Sales, Delivery, Marketing, Finance, Legal, and Customer Success. The role drives scalable workflows, reliable revenue data, AI-enabled pipeline and forecasting solutions, and technology adoption across the organization.

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.