Senior/Staff FDE - CUA
AI summary of the role
Snorkel AI is hiring a Senior/Staff Forward Deployed Engineer to lead technical execution of customer engagements involving computer-use agents (CUAs).
What you’ll do
- Design and build task environments, datasets, and evaluation workflows for computer-using agents
- Translate customer goals and agent failure modes into representative, multi-step tasks with clear success criteria
- Develop data-generation, validation, and QA pipelines for multimodal and agentic training/evaluation data
- Build automated evaluators and measurement frameworks to assess agent performance
What you’ll bring
- 5+ years in ML engineering, software engineering, applied AI, forward deployed engineering, or similar
- Strong Python skills and experience building reliable production software, data, or ML systems
- Hands-on experience building, evaluating, or deploying LLM-based or agentic systems, including computer-use agents
- Experience designing task environments, datasets, and verifiers for agents, including reward & verifier design
Technologies
Python · LLM · agentic systems · computer-use agents · RL with verifiable rewards · LLM-as-a-judge · multimodal models · browser automation · API development · data pipelines
About Snorkel AI
Data-centric AI platform and expert-data provider that helps enterprises and frontier labs build, evaluate, and tune specialized models and agents.
Series D
Source and classification
Implementation & delivery · Evidence for this classification:
Computer Use Agents to partner with leading AI labs and enterprises on their most critical agentic-AI initiatives. In this role, you will lead the technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks. You will translate ambiguous product and model challenges into robust task environments, datasets, evaluators, and delivery plans that improve agent reliability and downstream performance. You will work across the full delivery lifecycle—from technical discovery and solution design through implementation, evaluation, and production delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements. Main Responsibilities Computer Use Agents, Data, and Evaluation Design and
More from the job description
About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is hiring a Forward Deployed Engineer focused on Computer Use Agents to partner with leading AI labs and enterprises on their most critical agentic-AI initiatives. In this role, you will lead the technical execution of complex customer engagements involving agents that operate computers, browsers, and software environments to complete realistic, multi-step tasks. You will translate ambiguous product and model challenges into robust task environments, datasets, evaluators, and delivery plans that improve agent reliability and downstream perfor [... source excerpt omitted ...] uction delivery. You will also identify patterns across engagements and turn successful approaches into reusable capabilities, technical standards, and product improvements. Main Responsibilities Computer Use Agents, Data, and Evaluation Design and build task environments, datasets, and evaluation workflows for computer-using agents operating across browsers, desktop applications, terminals, and other software interfaces Translate customer goals, agent failure modes, and real-world workflows into representative, multi-step tasks with clear success criteria Develop data-generation, validation, and quality-assurance pipelines for multimodal and agentic training and evaluation data [... source excerpt omitted ...] o improved tasks, data, and evaluations Design and run experiments to measure how data, task design, and evaluation changes affect downstream agent performance Deliver reusable, production-grade task suites, datasets, and evaluation assets that help customers train, benchmark, and improve computer-use agents Forward Deployed Engineering & Customer Partnership Lead technical workstreams from initial solution design through production delivery, navigating ambiguity and making sound technical decisions Build, refine, and iterate on solutions that address customer needs, incorporating feedback to ensure the delivered work provides tangible value Rapidly prototype and productioniz
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