Snorkel AI is hiring a Manager, Forward Deployed Engineering to build and lead our Forward Deployed Engineering (FDE) function within the Data-as-a-Service (DaaS) organization
This team is responsible for the technical execution layer of DaaS delivery — owning the systems, workflows, and quality frameworks that power high-quality dataset production at scale
You will lead a team of engineers who operate across the full AI data lifecycle: designing evaluation systems, building ML-assisted workflows, and developing the technical foundations that make human-in-the-loop (HITL) data generation faster, more reliable, and scalable
This is a hands-on, player coach role where you’ll both help define the strategy and architecture of our data pipelines while staying close to implementation. As a founding leader, you will establish how FDE partners with Delivery, Engineering, and Research to ensure consistent, high-quality execution across all DaaS projects
You’ll operate at the intersection of data engineering, ML engineering, and production operations, driving the evolution of our technical delivery capabilities and enabling Snorkel to scale its impact across increasingly complex AI workloads
Build and lead the Forward Deployed Engineering function, defining the team’s operating model, technical roadmap, and standards for execution
Hire, mentor, and develop a high-performing team, fostering strong ownership, velocity, and engineering excellence
Own the design and evolution of end-to-end AI data pipelines, including dataset generation, evaluation systems, and quality frameworks
Drive development of ML-assisted and HITL workflows that improve the speed, scalability, and reliability of data production
Establish and standardize measurement, benchmarking, and validation systems to ensure consistent, high-quality dataset delivery
Develop scalable internal tooling and workflows for orchestration, monitoring, and delivery, reducing bottlenecks and improving throughput
Partner cross-functionally with Delivery, Engineering, and Research to productionize new approaches and continuously improve DaaS capabilities