About the role

Aplyr's Quick Take

This is a summer internship for PhD students focused on advancing robot learning and autonomy. You'll work on designing experiments and developing learning pipelines for real robotic systems, collaborating closely with researchers and engineers. It's an individual contributor role with a strong emphasis on practical applications of AI in robotics.

Good fit

Ideal candidates are current PhD students in relevant fields with research experience in robot learning or machine learning. You should be self-motivated, able to work independently, and have a keen interest in applying theoretical knowledge to real-world robotics.

Worth noting

The internship offers hands-on experience with deployed robotic systems, which is a significant plus for those looking to bridge research and practical applications. The role requires familiarity with ROS or ROS 2, which might be a barrier for some applicants.

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 journal
Ability to work independently while collaborating effectively in a research environment.
Strong interest in embodied intelligence and real-world robotics systems.

The Extras That Set You Apart

Prior experience working with real robot platforms.
Familiarity with ROS or ROS 2.
Experience with large-scale or distributed training systems.
Publications or open-source contributions in robotics or AI.
Background in perception, planning, or control for robotics.
Interest in bridging foundational research with deployed robotic systems.

Skills & Tags

go machine learning ai data design

Aplyr's read

Field AI is at the forefront of AI innovation, attracting talent passionate about transforming industry operations through advanced technology solutions.
Synthesized from recent postings & public sources

What's promising

•Strong focus on AI solutions enhances industry-specific operational efficiency.
•Diverse roles indicate robust growth and development opportunities.
•Involvement in federal projects suggests stability and long-term contracts.

What to watch

•High specialization may limit roles to highly skilled professionals.
•Potentially high-pressure environment due to cutting-edge projects.
•Limited public information about company culture and employee satisfaction.

Why Field AI

•Specializes in multimodal AI/ML engineering roles.
•Engages in federal projects, offering unique challenges and experiences.
•Focus on edge model optimization differentiates its AI deployment strategy.

Aplyr’s read is generated by AI from public sources. Was it useful?

About Field AI

Field AI

fieldai.com

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Field AI is a technology company specializing in artificial intelligence solutions for various industries, focusing on enhancing operational efficiency and decision-making processes.