Robotics Research Intern, Robot Learning (Summer 2026) | PhD Internship

Benefits

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Entry From the posting source checked Jun 20, 2026

Schedule

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Weekend work

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Company

Company stage

Growth-stage From the posting source checked Jun 20, 2026

Application

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Deadline

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About this role

Robotics Research Intern, Robot Learning (Summer 2026) | PhD Internship Pittsburgh, PA Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. We are offering a Summer 2026 internship in Robot Learning for students interested in advancing embodied intelligence through large-scale learning, foundation models, and real-world robotic deployment. As a research intern, you will work closely with FieldAI researchers and engineers to explore novel approaches to robot learning and autonomy, with a focus on scalable methods that generalize across tasks and embodiments. This internship is designed for PhD students who want to connect cutting-edge AI research with practical robotics systems. You will have the opportunity to design experiments, develop learning pipelines, and validate ideas on real robotic platforms, contributing directly to FieldAI's deployed autonomy stack. What You Have: Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field. Research experience in robot learning, reinforcement learning, imitation learning, or related areas. Strong foundation in machine learning fundamentals and experimental methodology. Develop multi-modal data collection platform for day/night robot navigation data collection Collect high-quality datasets for reproducible and comparable research and evaluation Summarize and publish learnings in high-quality robot research conference or

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