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Develop and optimize methods, algorithms, and systems for reliable AI agents in production environments. Collaborate with product and engineering teams to translate research prototypes into practical enterprise applications.
Join a team building infrastructure for reliable AI agents in production. You will advance agentic AI research and turn new methods into practical systems for enterprise workflows.
Develop and improve methods, algorithms, and systems across the lifecycle of reliable AI agents.
Create new approaches for simulating, evaluating, and optimizing agent behavior in real-world settings.
Turn research ideas into working prototypes and production-facing capabilities.
Partner with product and engineering teams to bring AI research 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 experience ranging from early-career to senior research backgrounds.
Research or professional experience with AI agents, agent frameworks, agent evaluation, or novel applications of agents.
Original research with observable outputs, such as publications, and a record of leading work from idea through execution.
Strong Python proficiency and expertise in AI/ML, LLMs, reinforcement learning, evaluation systems, or continuous learning.
Research depth and independent technical thinking, along with experience translating research into production systems.
Experience in an AI research lab, applied AI company, startup, or small team is relevant.
Base salary: $130,000 to $200,000 USD annually. Visa sponsorship is available.
Remote within the United States.
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