NVIDIA is seeking an Engineering Manager to lead our machine learning engineers within the Isaac Loco-Manipulation team. You will manage a group of world-class robotics researchers and engineers focused on advancing humanoid loco-manipulation and mobile manipulation, shaping the future of intelligent robotics.
What you’ll be doing:
Lead, mentor, and grow a high-performing team of applied research engineers focused on humanoid loco-manipulation and mobile manipulation.
Drive the definition, planning, and execution of projects involving foundation models (GR00T, Cosmos), Isaac Lab, and Newton workflows.
Guide the team in advancing robot learning technologies and synthetic data generation from human video datasets.
Hands-on design, implementation, and deployment of novel algorithms for humanoid robot locomotion and manipulation in simulation and real-world environments.
Ensure seamless integration of applied research outputs with NVIDIA’s advanced robotics platforms.
Foster a culture of innovation and collaboration, supporting deliverables such as prototypes, open source software contributions, patents, and publications in top conferences and journals.
Collaborate cross-functionally with product, hardware, and software teams to translate research into impactful products.
Support career development, performance management, and recruitment of top talent.
What we need to see:
Advanced degree (PhD or Master’s) in Computer Science, Robotics, or a related field.
2 years of experience on technical leadership or team management in robotics, autonomous driving, machine learning, or related domains.
Strong hands-on programming skills in Python and C++; experience with deep learning frameworks (PyTorch, JAX, TensorFlow) and physics simulation tools (Isaac Sim/Lab, MuJoCo).
Excellent communication, organizational, and interpersonal skills.
Experience with large-scale model training on GPU clusters.
Hands-on experience on robotics simulation, sim-to-real and real-to-sim transfer.
5+ overall years of experience working on robotics technologies.
Ways to stand out from the crowd:
Leadership in projects involving foundation models for robotics, including Vision-Language-Action (VLA) or Vision-Language Models (VLM).
Experience with learning from human video demonstrations and human-object reconstruction.
Expertise in humanoid loco-manipulation, encompassing whole-body control, dexterous and bimanual manipulation, and locomotion.
Advanced knowledge in robot learning and reasoning, including imitation and reinforcement learning.
Experience generating synthetic data for robotics applications.