Research Scientist

🔸 Research Engineer / Scientist - Agentic AI

🔸 San Francisco Bay Area

🔸 Autonomous Agents / Foundation Models / Scientific Reasoning

🔸 Competitive Base \+ Bonus \+ Meaningful Equity

PLEASE CONNECT WITH THE JOB POSTER AND FOLLOW THE KENKOTECH PAGE

About the Role

Our client is building advanced AI systems designed to accelerate scientific research and discovery.

They are hiring a Research Engineer / Research Scientist to help build autonomous AI systems that can actively participate in scientific R\&D workflows - generating hypotheses, gathering information, reasoning through complex problems, using tools, and helping researchers move faster from question to insight.

This is a highly interdisciplinary role sitting at the intersection of agentic AI, foundation models, machine learning, software engineering, and scientific discovery.

What You'll Do

• Design and build autonomous AI agents capable of reasoning through complex scientific workflows
• Develop tool-use systems, retrieval architectures, memory systems, and orchestration frameworks
• Build multi-step workflows that combine foundation models with external tools, databases, and scientific resources
• Create evaluation frameworks and benchmarks for measuring agent performance and scientific reasoning capabilities
• Improve model performance through prompt engineering, post-training, retrieval, reinforcement learning, or related techniques
• Work closely with researchers and domain experts to translate scientific workflows into scalable AI systems
• Help define the long-term architecture for production-grade scientific agents

Ideal Candidate Qualifications

• Strong experience building agentic systems rather than simply consuming foundation model APIs
• Hands-on experience with agents, tool use, workflow orchestration, memory systems, RAG, or multi-step reasoning systems
• Strong software engineering skills with the ability to design and deploy production systems
• Experience working with large language models, foundation models, or multimodal AI systems
• Experience designing evaluation frameworks, benchmarks, or model quality systems
• Strong Python skills and familiarity with modern ML frameworks
• Ability to work independently in highly ambiguous environments and drive projects from concept through deployment

Why Join?

• Opportunity to work on one of the most ambitious applications of AI to scientific discovery
• Small, highly technical team operating at the frontier of foundation models and autonomous systems
• Significant ownership and influence over core product and research direction
• Access to large-scale compute, proprietary datasets, and challenging real-world scientific problems
• Chance to help define how AI systems collaborate with scientists in the future