Research Scientist Intern (Enterprise AI Agent) - 2026 Start (PhD)

About the team

We are seeking an exceptional Research Scientist Intern to join our team to pioneer the next generation of Enterprise Agentic Solutions and Self-Evolving AI Agents. This role bridges cutting-edge research with production impact. You will work with proprietary internal datasets (including USDS and compliance-restricted environments) to design, evaluate, and deploy autonomous agents that offload routine workflows in engineering development, operations (DevOps/SRE), and product growth. Your goal is to deliver measurable speedups in project execution, significantly reduce operational expenditure, and publish high-impact research papers on enterprise agentic architectures.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.

Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.

Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).

Responsibilities

• Conduct cutting-edge research in self-improving agents, evolutionary optimization, and multi-agent systems to enable autonomous code generation, system maintenance, and decision-making.
• Formulate novel research ideas, design rigorous methodologies, conduct experiments, and lead papers for top-tier AI/ML conferences.
• Investigate methodology for agentic self-evolution using proprietary, compliance-restricted datasets (USDS), solving challenges around data safety, memory optimization, and long-horizon runtime stability.
• Develop robust evaluation frameworks to measure the concrete operational impact (e.g., runtime efficiency, task completion speedup, labor cost offloading) of agentic solutions in engineering and growth environments.

Minimum Qualifications

• Currently pursuing a PhD in Computer Science, Computer Engineering, or a related technical discipline.
• Expertise in one or more of the following research domains: AI Agents & LLM Tool Use / Harness Engineering, Reinforcement Learning & Evolutionary Algorithms / Genetic Programming, Code Generation, Automated Software Engineering, or Self-Improving Systems
• Strong implementation skills in Python, paired with system-level language proficiency (Rust, C++, or Go).

Preferred Qualifications

• Deep research exposure to iterative self-evolution paradigms (e.g., SGPO, recursive code improvement, execution-guided synthesis).
• Experience conducting research in restricted/internal data environments or handling compliance-sensitive execution loops.
• Demonstrated history of bridging high-impact theoretical research with rapid, functional open-source or production demos.