Senior/Staff FDE - CUA (Computer Use Agents)

Location: New York City, NY (Hybrid) or San Francisco, CA (Hybrid)

Salary: $180,000–$320,000 USD per year, plus variable compensation, equity, and benefits.

Company

Snorkel AI helps enterprises transform expert knowledge and data into specialized, production-ready AI systems.

What you will do

• Design and build task environments, datasets, and evaluation workflows for computer-using agents 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, quality-assurance, and automated evaluation pipelines for multimodal and agentic training and evaluation data.
• Diagnose failures across planning, tool use, perception, state management, and user-interface interaction, then improve tasks, data, and evaluators.
• Lead technical workstreams from solution design through production delivery and communicate tradeoffs, results, and recommendations to customers and stakeholders.
• Turn successful engagement solutions into reusable frameworks, tooling, standards, and product improvements while guiding other engineers.

Requirements

• 5+ years of experience in machine learning engineering, software engineering, applied AI, forward deployed engineering, solutions engineering, or a similar technical role.
• 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.
• Strong understanding of experimentation and evaluation, including LLM-as-a-judge, model-based evaluation, metrics, and empirical decision-making.
• Experience designing agent task environments, datasets, verifiers, and reward systems, plus working with APIs, automation, web applications, browsers, desktop applications, or developer tools.
• Ability to take ambiguous technical problems through implementation and delivery, set technical direction, create reusable approaches, and work directly with customers or cross-functional stakeholders.

Nice to have

• Experience developing agent benchmarks, task suites, or simulators.
• Experience with multimodal models, visual grounding, or agents interacting with graphical user interfaces.
• Experience with repo-scale agentic coding tasks, agent tool protocols, browser/computer-use products, or data pipelines for fine-tuning, reinforcement learning, preference optimization, benchmarking, or model evaluation.
• Experience in fast-paced customer-facing environments with evolving requirements and technical approaches.

Culture & Benefits

• Work in a rapidly scaling company with market-proven solutions and robust funding.
• Opportunities to shape priorities, influence strategic decisions, and contribute directly to company success.
• Support for deepening technical expertise, developing leadership skills, and learning across functions.
• Employee stock options and benefits are included in all offers.
• Equal employment opportunities and reasonable accommodation are provided.