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About the role
Gauntlet is looking for an AI Research Engineer to help improve how we build, evaluate and use AI agents across the business. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Hands-on experience building, evaluating or improving LLM models or agents, whether through professional work, applied research, open-source contributions or substantial personal projects
- Strong Python skills and good software engineering fundamentals. You're comfortable writing production-quality code and understand the importance of testing, maintainability and reliability
- Experience with applied research, machine learning or data science, including designing experiments, working with datasets and drawing conclusions from results
- A good understanding of how LLM agents work beyond prompting, including tool use, harnesses, context management and common failure modes
- The ability to take an open-ended problem, break it down into testable questions and work independently towards a solution
- Experience building tools or systems that other people use, with an understanding of how to evaluate their effectiveness beyond technical benchmarks
More about this role
Gauntlet is looking for an AI Research Engineer to help improve how we build, evaluate and use AI agents across the business.
We already have agents running in production, including Aria, our in-house generalist agent. They're used across research, engineering and business workflows, and we've learned a lot from seeing how they perform in practice. Some tasks work extremely well; others produce inconsistent results, and changes to models or tooling can introduce unexpected problems. Today, much of that feedback is still subjective. We want to build a more systematic way of understanding what works, what doesn't and why.
A major part of this role will be building the evaluation frameworks that allow us to measure agent performance on real tasks. You'll work with our engineers, quantitative researchers and other teams to understand where agents struggle, turn those observations into measurable experiments, and use the results to improve the systems we're building.
You'll also contribute directly to our existing agents and internal tooling. Initially, the work will be more engineering-focused as you get familiar with our systems, shipping improvements and integrations that teams can...
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