Software Engineering Manager, Robotics Neural Reconstruction And Real2Sim Applications

at Nvidia

USD 224,000-431,200 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Algorithms Communication @ 6 Deep Learning @ 4 GPU @ 4 JAX @ 7 Leadership @ 6 Machine Learning @ 6 PyTorch @ 7 Python @ 7 Reinforcement Learning @ 3 Robotics @ 4 Team Management @ 6 Technical Leadership @ 6 TensorFlow @ 7

Lead, mentor, and grow a high-performing team of robotics software and applied research engineers focused on robotics Neural Reconstruction & Real2Sim Applications.
Drive the definition, planning, and execution of projects involving 3D reconstruction, Digital twin creation, and robot simulation & validation tools.
Guide the team in advancing Real2Sim and its integration in robot learning developments.
Hands-on design, implementation, and deployment of novel algorithms for Neural Reconstruction, Real2Sim and their real-world applications & validation.
Collaborate & support other Isaac teams including Sim/Lab, Platform and SQA to deploy, validate, extend and release the capabilities & features on physical robots as well as on at-scale simulations.
Ensure effective integration, validation and releases of applied research efforts in collaboration with research teams and on top of NVIDIA’s advanced robotics platforms.
Foster a culture of innovation and collaboration, supporting deliverables such as prototypes, open source software contributions, patents, and publications.
Collaborate cross-functionally with product, hardware, and software teams to translate engineering work into impactful products.

PhD or Master’s degree in Computer Science, Robotics, or a related field (or equivalent experience).
8+ overall years of experience working on robotics and deep learning technologies.
3+ years of experience in technical leadership or team management in robotics, autonomous driving, machine learning, or related domains.
Strong hands-on programming skills in Python and/or C++; experience with Deep Learning frameworks (PyTorch, JAX, TensorFlow) and physics simulation tools (Isaac Sim/Lab, MuJoCo).
Excellent communication, organizational, and interpersonal skills.
Familiarity with robot learning, including imitation or reinforcement learning, and robot perception.
Experience with robot simulation tools & on robot deployments.

Leadership in projects involving Neural Reconstruction and/or Generative Simulations.
Experience with large-scale model training on GPU clusters.
Hands-on experience on robotics simulation, sim-to-real and real-to-sim transfer.