Snorkel AI

Research Engineer

• Own the infrastructure that powers model training and evaluation work
• Build and operate GPU cluster infrastructure, training pipelines
• Translate training requirements into robust, reproducible systems
• Monitor and optimize cluster health, inter-node communication
• Work closely with research scientists and ML engineers

Applied Research Engineer – Training Infra

Product Manager

• Own the product vision, strategy, and roadmap for the task and Expert Contributor Evaluations product supporting internal and external platform users.
• Identify bottlenecks and lead cross-team efforts to improve overall quality and customer acceptance rate.
• Lead Evaluation products and tools across research, engineering, operations, and forward deployed engineers to drive excellence in product quality.
• Define, build, and set up continuous monitoring for performance metrics of Evaluations to improve their adaption, usage, and effectiveness.
• Own the strategy and execution of Expert Contributor Quality
• Build a recommendation system for optimal matching of ECs to tasks on the Snorkel Platform
• Work with cross-functional stakeholders to support enablement and adaptation initiatives of the Evaluations and Quality products
• Balance short-term delivery with long-term platform investments to support future growth.

Senior Product Manager – Data, Quality

Product Marketing

• Design and implement a comprehensive enablement roadmap
• Develop competency-based onboarding and certification programs
• Partner with the Marketing Leadership to turn messaging into strategies
• Establish a knowledge base in Notion and explore LMS integration
• Collaborate with DaaS leadership and Cross-functional partners

Operations Manager – Enablement GTM, Presales

Solutions Engineer

• Partner with frontier AI research labs to design datasets and environments that improve model performance
• Lead technical conversations with customer researchers to understand model capabilities, failure modes, data requirements, and success criteria
• Probe model behavior through systematic evaluation to uncover weaknesses and identify high-impact data interventions
• Design evaluation frameworks, calibration processes, and quality rubrics that establish measurable project success metrics
• Develop technical specifications for data projects that balance research rigor with operational feasibility
• Serve as thought partner to customer research teams throughout the sales cycle, building trust and credibility
• Stay current on frontier AI research, RL environment design, post-training techniques, and evaluation methodologies

AI Solutions Engineer – Data as a Service

• Own the product vision, strategy, and roadmap for the core platform supporting expert contributors, internal operations, and customers.
• Define and deliver expert tooling, workflow orchestration systems, and internal ops controls that improve productivity, quality, and scalability.
• Lead platform initiatives across data ingestion, storage, versioning, permissions/IAM, and system reliability.
• Partner deeply with Engineering to make informed tradeoffs across APIs, data models, system architecture, and platform abstractions.
• Collaborate with Research and Operations to ensure platform capabilities support evolving RLHF methodologies and operational needs.
• Build and evolve APIs and SDKs that enable customers to seamlessly access the platform capabilities.
• Drive metrics across throughput, cycle time, quality, cost efficiency, platform adoption, and reliability.
• Identify platform bottlenecks and lead cross-team efforts to improve performance, scalability, and experts experience.
• Balance short-term delivery with long-term platform investments to support future growth.

Senior Product Manager – Platform

Operations

• Partner closely with the GM of DaaS to define and execute the overall DaaS strategy.
• Own and drive core operating rhythms for the DaaS business (e.g., WBRs, planning cycles, performance reviews).
• Act as a GM for select strategic bets or initiatives, owning outcomes end to end.
• Lead high-impact, cross-functional initiatives that cut across Product, Delivery, Supply, Sales, Finance, and Engineering.
• Hold the pen on DaaS strategy, including identifying key bets, tradeoffs, and growth opportunities as the business scales.
• Step in to temporarily own functions or problem spaces until permanent teams or leaders are hired.
• Build and manage a small, high-performing Strategy & Ops team as the organization grows.
• Use data and analysis to inform decision-making, track performance, and surface risks and opportunities early.

Head of DaaS Strategy – Operations

People Operations

• Own and scale high-impact people programs
• Lead the end-to-end design, execution, and continuous improvement of core people programs, including: New hire journey, Growth (performance) cycles, Manager enablement and development, Individual contributor learning and development
• Design programs with employee experience and growth as a core priority, ensuring each touchpoint feels intentional, inclusive, and aligned with Snorkel’s culture.
• Serve as a key in-person facilitator and host for onboarding sessions, manager training, and learning experiences, bringing enthusiasm, warmth, and energy to how Snorkelers experience People programs.
• Ensure programs are operationally excellent, delivered on time, and clearly communicated.
• Support change management as programs evolve, driving adoption and shared understanding while remaining pragmatic and nimble for our size and stage.
• Build and manage detailed program plans, timelines, and dependencies across multiple initiatives.
• Bring creativity and fresh thinking to your program design, providing innovative ideas and solutions to the key lifecycle programs that employees and managers experience here.
• Coordinate cross-functional stakeholders to ensure smooth and effective execution.
• Anticipate risks, resolve issues, and lead retrospectives to improve future iterations.
• Partner closely with the HRBP team to design tools, training, and live learning experiences that help managers lead effectively.
• Create clear documentation, playbooks, and manager-facing resources that are practical and easy to apply.
• Support managers through critical moments such as performance reviews, feedback and coaching conversations, and compensation discussions.
• Define success metrics for people programs and evaluate impact using both qualitative and quantitative feedback.
• Analyze surveys, participation metrics, and retrospectives to identify insights and drive continuous improvement.
• Partner with the People Data and Operations Manager on reporting and measurement.

People Programs Manager

AI Research Scientist

• Recruit for and lead a team of applied researchers, setting the team’s culture and setting a high standard for quality and velocity
• Act as the primary link between Research, Product, and Engineering. Oversee the development of experimental POCs to improve workflow efficiencies and ensure these innovations are successfully hardened and integrated into the platform
• Collaborate with academic and industry-leading AI labs to define the data-centric techniques that will help power the next generation of foundation models
• Anticipate the next bottlenecks in the AI data and pivot the team to develop programmatic solutions that address them
• Partner with the Operations team to validate research-driven workflows in real-world production environments, ensuring they scale across diverse and complex domain-specific tasks