AI Research Scientist
About The Position
Our client is a nine-person AI infrastructure startup building the systems that make autonomous agents reliable in production. Founded in 2024, the company turns agent failures, traces, evaluations, and human feedback into replayable learning environments with regression control inside the optimization loop. It has raised $6.9M and already supports large enterprise customers across financial services, healthcare, and technology. We are hiring an AI Research Scientist to advance the frontier of reliable agentic AI. You will be a core contributor to original methods for agent simulation, evaluation, optimization, and continuous learning, while remaining hands-on enough to turn research ideas into working systems and production-facing capabilities. Research depth is the priority, with real product impact and close collaboration across a small technical team.
Requirements
- A PhD in computer science, machine learning, or a closely related field, or equivalent research depth
- At least one year of research experience focused on LLM agents or agentic systems
- Expertise in evaluations, novel applications of AI agents, or agent frameworks
- Strong publication evidence at venues such as NeurIPS, ICLR, ICML, or ACL, or meaningful contributions to widely used open-source projects
- Proficiency in Python and the ability to implement research ideas hands-on
- Independent research judgment and the ability to clearly explain your personal contributions
- Availability to work East Coast hours from the United States or Canada
Nice To Haves
- Experience as a first research hire or member of a small startup research team
- Research experience at an AI lab or applied AI company
- Experience translating AI research into production systems and enterprise products
- Familiarity with reinforcement learning, continuous learning, simulation systems, or agent optimization
- A fresh PhD is welcome if the research fit and hands-on ability are strong
Responsibilities
- Develop new methods, algorithms, and systems across the lifecycle of reliable AI agents
- Create novel approaches for simulation, evaluation, optimization, and regression control in real-world agent settings
- Study agent failures, traces, and human feedback to design more reliable learning loops
- Turn research ideas into experiments, prototypes, and production-facing capabilities
- Partner with product and engineering teams to translate frontier AI work into customer value
- Help define the company's technical direction in agent reliability, evaluation, and optimization
- Contribute independent ideas and challenge assumptions with rigorous experimental evidence
Benefits
- Approximately 1% equity
- Direct collaboration with recognized researchers and repeat founders
- Visa transfers, STEM OPT, H-1B transfer, or TN support may be available
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
