Data AI · Data-centric ML
Currently tracking 20 active AI roles, up 38% versus the prior 4 weeks. Primary focus: Data · Engineering. Salary range $150k–$350k (avg $244k).
| Title | Stage | AI score |
|---|---|---|
| Senior Product Manager - Data & Quality Senior Product Manager at Snorkel AI to lead development for agentic data systems, synthetic data systems, evaluations, and data-acceleration initiatives. The role involves defining product vision, roadmap, and execution plans for intelligent workflow systems, optimizing data pipelines, and improving task quality. Key responsibilities include owning the product vision for task and evaluation products, leading evaluation initiatives, defining performance metrics, building recommendation systems for task matching, and supporting enablement efforts. | Eval GateData | 8 |
| Strategic AI Lead This role leads high-stakes Data-as-a-Service programs end-to-end, acting as the CEO of the program. It involves owning the P&L, managing stakeholders (clients, internal teams, expert contributors), designing training data programs, developing and scaling the contributor network, building systems from scratch, monitoring performance, driving communications, managing data flows, and operating with urgency to ship better models. The role requires ML intuition for training data quality and evaluation design, and strong operational skills for managing complex programs at scale. | Data | 7 |
| Technical Delivery Manager Snorkel AI is seeking a Technical Delivery Manager (TDM) to lead high-stakes Data-as-a-Service programs end-to-end. This role involves owning the program's success, including P&L, quality, timelines, and margin. The TDM will translate technical requirements into executable programs, design training data programs with clear task definitions and evaluation criteria, develop and scale the Expert Contributor Network, build and harden workflows and quality systems, monitor performance with data-driven insights, and manage internal/external communications. The role requires ML intuition for training data and evaluation, comfort with data manipulation (SQL, JSON, Python), and a strong bias for action in ambiguous, fast-changing environments. | Data | 7 |