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Develop and improve AI methods and systems to ensure the reliability of AI agents in production environments. Collaborate with product and engineering teams to translate research prototypes into practical, production-facing capabilities.
Advance research and practical methods for making AI agents reliable in production. You will contribute to the technical direction of an AI agent platform, connecting new research in agent behavior, evaluation, and optimization with systems that work in real-world settings.
Develop and improve AI methods, algorithms, and systems across the lifecycle of reliable agents.
Design new approaches to simulate, evaluate, and optimize agent behavior in real-world environments.
Turn research ideas into prototypes and production-facing capabilities.
Partner with product and engineering teams to bring AI advances into practical applications.
Help shape technical direction in agent reliability, evaluation, and optimization.
A PhD in computer science, machine learning, or a related field, with 1 to 10+ years of relevant experience; recent PhD graduates are welcome.
Research or professional experience with AI agents, agent frameworks, or novel agent applications, including a track record of research outputs such as publications.
Publications in leading AI or machine learning venues are a plus.
Strong Python skills and familiarity with LLMs, reinforcement learning, evaluation systems, and continuous learning.
Research depth, independent ideas, and the ability to challenge existing approaches.
Experience translating research into production systems; small-team or startup experience is useful.
Base salary: $130,000 to $200,000 USD annually. Visa sponsorship is available.
Remote within the United States.
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