1.77 Robotics Research AI Engineer: Robot Learning

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.

**About the Job

We are looking for a Robotics Research AI Engineer (Robot Learning) to push the frontier of embodied intelligence. In this role, you will design and deploy cutting-edge learning algorithms that enable robots to acquire new skills across a wide range of embodiments. You will contribute to research and large-scale training of foundation models for robotics, spanning visual-language models (VLMs), large language models (LLMs), and control policies. Your work will directly impact robot capabilities in the field, from traversability to dexterous manipulation, shaping how intelligent robots operate in unstructured real-world environments.

This is a role for someone who thrives at the intersection of research and engineering—building scalable learning systems while advancing state of the art in robot learning.

What You'll Get To Do

• Develop Robot Skill Learning Methods
• Design and train algorithms that enable robots to acquire generalizable skills across diverse embodiments

• Integrate reinforcement learning, imitation learning, and foundation models into real robot pipelines

• Advance Robotics Foundation Models

• Leverage and adapt VLMs and LLMs to robotics tasks, including perception, reasoning, and action planning

• Explore large-scale pretraining and fine-tuning approaches tailored to embodied intelligence

• Large-Scale Training and Deployment

• Build and optimize large-scale distributed training pipelines using PyTorch and modern ML infrastructure

• Deploy models onto real robots, bridging the gap between simulation and field-ready execution

• Real-World Robotic Applications

• Work on core challenges in traversability, mobile robotics, and manipulation

• Collaborate with hardware engineers to validate algorithms in unstructured, high-variance environments

• Research and Publication

• Conduct cutting-edge research and publish in top robotics, AI, and machine learning venues
• Contribute to the broader robotics research community while advancing Field AI's mission

What You Have

• Strong research background (PhD, MS, or equivalent industry research experience) in Robotics, AI/ML, or related fields
• Proficiency in robot learning methods (reinforcement learning, imitation learning, representation learning)
• Experience with PyTorch and modern ML training frameworks
• Hands-on experience with real robots (mobile platforms, manipulators, or other embodiments)
• Strong foundation in large-scale distributed training and optimization
• Ability to translate research into practical, field-deployable systems
• Excellent problem-solving skills and ability to thrive in fast-paced, interdisciplinary teams

The Extras That Set You Apart

• Publications in top-tier conferences/journals (CoRL, ICRA, IROS, NeurIPS, ICML, CVPR, etc.)
• Experience deploying VLMs/LLMs in robotics pipelines
• Background in 3D vision, mapping, or traversability analysis
• Experience in sim-to-real