AI Researcher
Conduct applied research on AI agents, designing experiments and evaluation systems to improve reliability, context retention, and multi-step task completion. The role requires strong AI/ML research, engineering, experimental design, and communication skills.
About the job
Responsibilities
- Design and run experiments to evaluate agent reliability, context retention, multi-step task completion, and failure modes.
- Build and own an evaluation layer that measures whether agents complete work correctly, not merely whether their outputs sound plausible.
- Research advances in LLM agents, tool use, and reliability, and translate findings into product and engineering decisions.
- Provide clear, actionable recommendations that engineering can implement.
- Prototype promising research ideas into working product features and hand off validated solutions.
- Shape the research roadmap as the company grows.
Requirements
- Track record of applied AI/ML research, ideally involving LLM applications, agentic systems, evaluations, or production AI reliability.
- Strong experimental design and analytical skills.
- Strong engineering fundamentals and ability to prototype experiments independently.
- Deep familiarity with LLMs, tool use, context management, and agentic-system failure modes.
- Strong written communication and ability to turn research into action.
- Pragmatic, rigorous approach to determining when findings are actionable.
- Comfort working with ambiguity and unsolved problems.
- Ability to use AI agents to accelerate research and implementation.
- Willingness to ship practical solutions.
Nice-to-haves
- Experience with LLM evaluations, hallucination mitigation, or production AI reliability at scale.
- Experience building or evaluating agentic systems, tool use, or autonomous workflows.
- Public research or engineering work, such as papers, open-source projects, blog posts, or side projects.
- Experience with product-led research focused on shipped features.
Skills
Artificial Intelligence, Machine Learning, LLMs, AI Agents, Llm Evaluation, Experimental Design, Tool Use, Context Management, Python, Autonomous Workflows
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