About the Role
Join an AI/ML team building tools to make production AI agents more reliable. You will own the intelligence that identifies agent failures, assesses confidence, and checks whether proposed fixes work.
What You'll Do
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Detect subtle failures, including omissions, compliant but incorrect responses, and patterns that emerge across large volumes of traces.
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Turn user behavior signals, such as rephrasing, abandonment, and retries, into evidence of agent failures.
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Build evaluation methods to measure detection precision when labeled ground truth is limited or unavailable.
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Make patch generation trustworthy by reproducing failures, verifying proposed fixes, and avoiding low-confidence changes.
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Improve the cost efficiency of detection, choosing appropriate models and approaches for each event.
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Review production customer traces regularly to identify problems and opportunities for improvement.
What We're Looking For
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Demonstrated AI/ML engineering experience; candidates with 0 to 10 years of experience are welcome, including new graduates and people without a traditional degree.
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Hands-on experience using LLMs in production, including evaluations, LLM-as-judge, embeddings, and deciding when a smaller model or no model is appropriate.
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An individual-contributor engineering background and a track record of shipping products that people use.
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Strong research judgment and the ability to distinguish meaningful improvements from noise, especially when ground truth is unavailable.
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Experience running agents in production and learning from their failures is a plus.
Compensation & Benefits
Base salary: $120,000 to $200,000 annually. Visa sponsorship is not available.
Location
On-site in San Francisco, United States.
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