Staff Machine Learning Engineer, AgenticUnchain Data • Menlo Park, California, United States
Staff Machine Learning Engineer, Agentic
Unchain Data
- Menlo Park, California, United States
- Menlo Park, California, United States
About
The Agentic AI team builds agentic AI systems that power intelligent, reliable customer experiences across Robinhood products. The team focuses on reducing the time to ship agents with fine-tuned models while enabling other teams to build, evaluate, and improve their own agents.
As a Staff Machine Learning Engineer (IC6), you will define and uphold the quality bar for agentic systems across the organization. You will design evaluation frameworks, guide model selection, and partner with product, data science, and engineering teams to ensure systems meet clear standards for correctness, safety, latency, and user satisfaction. Your work will shape how agentic systems are built, evaluated, and improved across Robinhood.
This role is based in our Bellevue, WA or Menlo Park, CA office, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community.
Responsibilities
Define and implement evaluation frameworks that measure agent performance, including task success, correctness, tool usage reliability, latency, safety, and user satisfaction
Evaluate frontier and fine-tuned models across quality, latency, cost, and edge cases to determine appropriate use cases
Partner with product managers, data scientists, and engineers to translate evaluation results into clear launch criteria for agentic systems
Analyze production issues, identify root causes, and prioritize improvements to increase system reliability and performance
Build visibility into agent performance through metrics, monitoring, and reporting that inform roadmap decisions
Requirements
Deep experience defining and measuring quality for agentic or machine learning systems using evaluation frameworks, datasets, and scorecards
Experience evaluating large language models or similar systems, including understanding tradeoffs in performance, cost, and latency
Demonstrated ability to analyze production issues and lead initiatives that improve system quality across multiple teams
Comfortable working with engineers, data scientists, and product partners to deliver measurable improvements in system performance
Nice to Have
Experience building or operating systems in regulated environments
Working with AI evaluation and observability tools
Benefits
Challenging, high-impact work to grow your career
Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet – a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life and disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces
Compensation This role is also eligible for bonus opportunities, equity, and benefits in addition to base pay.
Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones.
Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)
$255,000 — $300,000 USD
Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)
$225,000 — $264,000 USD
Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)
$199,000 — $234,000 USD
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Languages
- English
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