AI Robotics Intern
ABB
This job at a glance
- Who can apply
- New grads and up to 1 year
- Must know
- Data structures & algorithmsData analysisTroubleshootingPythonDeep learningPyTorch
- Work
- On-site in Milpitas · internship
- Pay
- Not stated by the employer.
- Skill demand
- Python59%Troubleshooting22%Data structures & algorithms13%Data analysis6%of 99 similar entry-level jobs posted in the US this week
- Listed
- Oct 28, 2026 · still open
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About the Role
This is an AI Robotics Intern position for Fall 2026 within ABB's Robotics business. The role is onsite/hybrid in San Jose, CA and reports to an R&D Senior Engineer.
Key Responsibilities
- Design, develop, and evaluate AI algorithms for robotics perception, including object detection, instance segmentation, pose estimation, and foundation vision models.
- Evaluate emerging AI technologies, including vision foundation models, multimodal models, and Physical AI approaches, for industrial robotics use cases.
- Participate in hands-on robotics lab work, including setting up and modifying robotic workcells and supporting experiments and system integration.
- Work across both software and hardware aspects of robotics projects, from AI model development and data analysis to robot setup, testing, troubleshooting, and experimental validation.
- Collaborate with robotics, perception, and software engineers to integrate AI models into production-ready robotic systems.
- Analyze model accuracy, latency, robustness, and failure cases, and propose improvements through experimentation and data-driven evaluation.
- Contribute to technical documentation, design reviews, and presentations for internal engineering teams.
Requirements & Tech Stack
- Currently pursuing a Master's, or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field.
- Willing and comfortable working hands-on in a robotics laboratory, including physical setup of robotic systems, workcells, and experimental equipment.
- Curious, adaptable, and open to learning and contributing in technical areas outside of their primary expertise as project needs evolve.
- Strong programming skills in Python.
- Familiarity with modern software engineering practices.
- Experience with deep learning frameworks such as PyTorch.
- Solid understanding of machine learning and computer vision fundamentals.
- Strong analytical and problem-solving skills with the ability to independently investigate technical challenges.
- Excellent communication skills and ability to work effectively in a collaborative engineering environment.
- Experience training and evaluating deep learning models on custom datasets.
- Familiarity with GPU acceleration, CUDA, or model optimization for edge deployment.
- Experience with synthetic data generation, simulation, or data-centric AI workflows.