Agentic AI R&D Intern

Location: Sunnyvale, CA, us Employment Type: {'id': 'intern', 'label': 'Intern'}

Company Description

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design.

As part of the global research organization, our AI research in Silicon Valley focuses on Foundation Models and Gen AI, Human-AI Collaboration and Trustworthy AI, AI for Advanced Driver-Assistance Systems (ADAS) and Autonomous Systems, AI Systems Engineering, and Industry AI. We develop scalable, intelligent, and trustworthy AI solutions to enable inspiring user experiences for Bosch products and services in application areas such as ADAS, smart manufacturing, enterprise AI, healthcare, smart home, and building solutions.

Originating from Bosch AI research in Silicon Valley, our Agentic AI Research Group advances cutting-edge research in large language models (LLMs), AI agents, and intelligent autonomous systems. Our research spans autonomous and multi-agent systems, agent reasoning and planning, agent memory, self-improvement, retrieval-augmented generation (RAG), reinforcement learning, and multimodal foundation models. We aim to develop novel algorithms and systems that enable AI agents to reason, learn, collaborate, and act effectively in complex real-world environments. We actively collaborate with leading researchers and organizations across academia and industry to advance the state of the art in Agentic AI. Our work regularly contributes to internationally renowned conferences and journals, including NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, COLM, and TMLR.

Job Description

You will 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.

You will 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.

Responsibilities

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

Knowledge integration and grounding for agents

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

Conduct novel research in Agentic AI, LLMs, and related fields.

Design, implement, and evaluate research prototypes demonstrating innovative AI agent capabilities.

Collaborate closely with Bosch researchers and domain experts to address challenging industrial problems.

Analyze experimental results and identify opportunities for scientific innovation.

Publish research outcomes in top-tier AI conferences and journals, such as NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, and COLM.

Qualifications

Basic Qualifications

Currently enrolled in a Ph.D. or Master's program in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or a related field.

Strong 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

Strong programming skills in Python and experience with modern AI/ML framework

Familiarity with agent workflows involves tool use, function calling, retrieval, memory, and multi-step reasoning.

Experience conducting independent research, designing experiments, and analyzing results.

Strong written and verbal communication skills and ability to work effectively in a collaborative research environment.

Minimum GPA of 3.0

Preferred Qualifications

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 with retrieval-augmented generation (RAG), agentic retrieval systems, and knowledge-grounded agents.

Experience with multi-agent systems, agent collaboration, and distributed agent workflows.

Experience with multi-modal foundation models involving language, vision, and structured data.

Experience in reinforcement learning, online learning, or adaptive decision-making systems.

Experience with agent benchmarking, evaluation methodologies, reliability, safety, or alignment.

Experience in applying Agentic AI technologies to real-world domains such as engineering design, or industrial automation.

Open-source contributions or d