Bosch Group: Agentic AI R&D Intern — Sunnyvale, CA, United States

About Bosch Group

Bosch's India activities span mobility, industrial technology, consumer goods, and energy and building technology. Its employer description identifies engineering development, manufacturing and commercial operations within that range. The group operates through multiple Indian businesses, including activities in automotive systems, software and engineering, industrial technology and home appliances. This makes Bosch a collection of related technology businesses rather than a single product operation, with different entities serving different industrial and consumer applications.

The position and its setting

Bosch Group lists Agentic AI R&D Intern in Sunnyvale, CA, United States, under reference REF298112P. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Employment type: Intern
• Employer listing date: 23 October 2026
• Contract type: Unlimited
• Legal Entity: Robert Bosch LLC
• Brands: Bosch Group

Responsibilities and work described

• Work: on cutting-edge Agentic AI research while tackling real-world challenges in domains such as Industrial AI, Manufacturing, Mobility, and Smart Home
• Unlike purely academic environments, you will have the opportunity to develop and validate novel AI technologies on large-scale real-world applications with measurable impact
• Work: closely with experienced Bosch researchers in Silicon Valley and across our global research network, receive mentorship from leading AI experts, and help transform cutting-edge research into real-world AI systems deployed in industrial domains
• Depending on your expertise and interests, you will contribute to one or more cutting-edge research topics, including:
• Agent systems for industrial applications
• Autonomous AI agents and multi-agent systems
• Agent reasoning, planning, and decision making
• Agent memory and long-horizon task execution
• Agent self-improvement, continual learning, and adaptation
• Tool use, function calling, and agent-environment interaction
• Retrieval-Augmented Generation (RAG) and Agentic RAG
• LLM post-training, reinforcement learning, and test-time scaling
• Multi-modal agents leveraging language, vision, and structured data
• Human-agent collaboration and interactive AI systems
• Agent evaluation, benchmarking, reliability, and safety
• Key responsibilities include:

Essential requirements and candidate background

• Knowledge integration and grounding for agents
• Currently enrolled in a Ph.D. or Master's program in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or a related field
• Research background in Agentic AI, Large Language Models (LLMs), machine learning, natural language processing, or related areas
• Experience developing AI agents using modern frameworks and ecosystems
• Programming skills in Python and experience with modern AI/ML framework
• Familiarity: agent workflows involves tool use, function calling, retrieval, memory, and multi-step reasoning
• Experience conducting independent research, designing experiments, and analyzing results
• Written and verbal communication skills and ability to work effectively in a collaborative research environment
• Minimum GPA of 3.0

Preferred experience and additional strengths

• Publication record in top-tier AI, NLP, or machine learning venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, COLM)
• Research experience in LLM-based agents, agent architecture, task planning, reasoning, and autonomous decision making
• Research experience in agent optimization, including post-training, reinforcement learning, preference optimization, and self-improvement
• Experience: retrieval-augmented generation (RAG), agentic retrieval systems, and knowledge-grounded agents
• Experience: multi-agent systems, agent collaboration, and distributed agent workflows
• Experience: multi-modal foundation models involving language, vision, and structured data
• Experience: reinforcement learning, online learning, or adaptive decision-making systems
• Experience: agent benchmarking, evaluation methodologies, reliability, safety, or alignment
• Experience: applying Agentic AI technologies to real-world domains such as engineering design, or industrial automation
• Open-source contributions or demonstrated leadership in AI research communities

Location, schedule and contract conditions

For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.

• Work arrangement: On-site
• Advertised location: Sunnyvale, CA, United States

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Agentic AI R&D Intern vacancy is not an offer for reference REF298112P; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Bosch Group

Applications follow the official employer page linked below.

Open the official Bosch Group posting below and match the title and reference REF298112P.

Compare your qualifications and experience with the essential conditions for the Sunnyvale, CA, United States position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• AI/ML
• LLMs
• AI
• manufacturing
• training
• machine learning
• electrical engineering
• communication