AI Research Engineer – Legged Robot Locomotion
Position Summary
Ready to teach robots how to walk, run, and conquer the real world?
The IHMC robotics group in sunny Pensacola, FL, is looking for a creative and driven AI Research Engineer to join our team! We want you to use your passion for Machine Learning to bring our cutting-edge humanoid and quadrupedal robots to life. Your work will directly contribute to enhancing the agility, robustness, and adaptability of our robotic platforms, bridging the critical gap between simulation and the real world. You will test your ideas in advanced simulators and then deploy them on our state-of-the-art physical hardware.
We are a collaborative, passionate team focused on solving hard problems and making a tangible impact. If you are driven to push the boundaries of what’s possible and want to see your research come to life on real-world robots, we encourage you to apply.
Responsibilities
- Algorithm Development: Research, design, and implement machine learning algorithms for legged robot locomotion control, dynamic gait generation (e.g., walking, running, galloping), and complex behavior synthesis. Explore and apply other relevant ML techniques, as appropriate.
- Simulation & Testing: Utilize and potentially extend high-fidelity simulation environments, particularly NVIDIA Isaac Sim and MuJoCo, for rapid algorithm prototyping, policy training, and comprehensive evaluation. Develop and execute rigorous testing protocols within simulation to benchmark performance and identify potential issues before hardware deployment.
- Hardware Integration & Validation: Deploy, test, debug, and refine ML-based controllers on physical quadrupedal and humanoid robot platforms. Actively address the challenges associated with sim-to-real transfer to ensure reliable performance on hardware. This involves significant hands-on interaction with complex robotic systems.
- Data Analysis: Collect, process, and meticulously analyze data from both simulation and physical experiments. Use insights derived from data to evaluate algorithm performance, diagnose failure modes, and drive iterative improvements in controller design and robustness.
- Collaboration: Work closely and effectively within a multidisciplinary team environment, collaborating with researchers and engineers specializing in areas such as control theory, perception, mechanical design, software development, and human factors. Actively participate in brainstorming sessions, technical reviews, and knowledge sharing.
- Documentation & Dissemination: Maintain clear, comprehensive documentation of research activities, code implementation, experimental procedures, and results. Contribute to the preparation of research papers for publication in leading peer-reviewed robotics and AI conferences/journals, as well as internal technical reports and potentially project proposals.
Qualifications Summary
The table below summarizes the essential and desirable qualifications for this position. We encourage you to apply even if you don’t meet every desirable qualification; we value diverse experiences and the potential to learn and grow in the role.
| Qualification Category | Essential Qualifications | Desirable Qualifications |
|---|---|---|
| Education | Master’s degree in Computer Science, Engineering, or a closely related technical field. | Ph.D. in a relevant field with dissertation focused on AI/ML for robotics/locomotion. |
| Experience | Proven experience applying AI/ML to robotics or control systems. | Direct, hands-on experience deploying and debugging algorithms on physical legged robots. |
| Programming | Proficiency in Python, Java, C++, or other language. | Experience in the test-driven development process. |
| AI/ML Expertise | Solid theoretical understanding and hands-on experience with Reinforcement Learning (RL) and/or Imitation Learning (IL) techniques. | Experience with deep learning frameworks (PyTorch, TensorFlow) and related techniques (CNNs, RNNs/LSTMs, Transformers, Diffusion Models). |
| Simulation Tools | Demonstrable experience using modern robotics simulation platforms, specifically NVIDIA Isaac Sim or MuJoCo. | |
| Robotics Fundamentals | Solid grasp of core robotics concepts (kinematics, dynamics, control theory, state estimation). | Specific research or project experience in developing controllers for dynamic legged locomotion (walking, running, jumping, navigating uneven terrain). |
| Publications | N/A | Peer-reviewed publications in top-tier robotics (e.g., ICRA, IROS, RSS, Humanoids) or AI/ML (e.g., NeurIPS, ICML, CoRL) venues. |
Application Instructions
To apply for this position, please email the following materials to robotjobs@ihmc.org with the subject line “AI Engineer Position – YourLastName”:
- Current Resume: Submit in PDF format. Please name your file: “YourLastName_Resume.pdf”.
- Cover Letter: Submit in PDF format. Please name your file: “YourLastName_CoverLetter.pdf”. In your cover letter, please address:
- Your specific interest in this AI/ML Research Engineer role at IHMC.
- How your qualifications and experience, particularly in Reinforcement Learning, Imitation Learning, Isaac Sim, and robotics, align with the position requirements.
- Optionally, provide links to relevant materials such as a personal website, GitHub profile, project portfolio, or videos demonstrating your work (especially related to ML for robotics or simulation).
- Download this Pre-Interview Questionnaire.pdf, complete and sign the form (typed signature will not be accepted) and attach it. Name your file: “YourLastName_Questionnaire.pdf
- Professional References: Provide the names, email addresses, and phone numbers (work or cell) for three (3) professional references within your cover letter or resume.
Applications will be considered incomplete until all requested materials (Resume, Cover Letter including References) are submitted according to the specified format.
Questions regarding this position can be directed to robotjobs@ihmc.org.