Agentic AI R&D Intern: Autonomous Agents & LLMs

Bosch USA; Sunnyvale (CA); On-site; USD 73,000 - 96,000; Part time

Job summary

Bosch USA is seeking highly motivated graduate students for an internship in Agentic AI research at the Bosch Research and Technology Center North America in Sunnyvale, CA. You will work on agentic AI and large language models to develop systems with real-world industrial applications.

You will collaborate with seasoned researchers across the Bosch network, publish your findings at top AI conferences, and contribute to AI systems engineering, multi-modal agents, and safety in complex

Qualifications

• Currently enrolled in a Ph.D. or Master's program in CS/CE/EE/AI.
• Strong research background in Agentic AI, LLMs, ML or NLP.
• Experience developing AI agents using modern frameworks.
• Strong Python programming skills and familiarity with AI/ML frameworks.
• Familiarity with agent workflows: tool use, function calling, memory, and multi-step reasoning.
• Excellent written and verbal communication; GPA minimum 3.0.

Responsibilities

• Research novel Agentic AI topics and publish findings in top venues.
• Design and evaluate prototypes demonstrating AI agent capabilities.
• Collaborate with Bosch researchers and domain experts on industrial problems.
• Analyze results and identify opportunities for scientific advancement.
• Contribute to NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, COLM conferences or journals.

Skills

Agentic AI research

Python programming

ML/NLP fundamentals

Independent research

Technical communication

Education

Ph.D. or Master's in CS/CE/EE/AI

Tools

Python

AI frameworks

Job description

Bosch USA is seeking highly motivated graduate students for an internship in Agentic AI research at the Bosch Research and Technology Center North America in Sunnyvale, CA. You will work on agentic AI and large language models to develop systems with real-world industrial applications.

You will collaborate with seasoned researchers across the Bosch network, publish your findings at top AI conferences, and contribute to AI systems engineering, multi-modal agents, and safety in complex