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What You Will Be Doing
Deploy algorithms on real humanoid robots to evaluate sim2real transfer.
Build and optimize data generation pipelines for training and validating robotic models.
Implement and enhance robot learning algorithms for robotics.
Focus on humanoid loco-manipulation tasks to advance robotic capabilities.
PerformVision-Language-Action(VLA) pre-training and post-training.
Collaborate with engineering and research teams to enable foundation models on humanoid robots.
Run experiments and analyze results to improve robotic system performance.
Continuously learn and explore new technologies.
What we need to see:
Master’s degree or PhD in Computer Science, Robotics, Electrical Engineering, or a related field (or equivalent experience)
8+ Years of experience inrobotics, embedded systems, or related domains.
Proficient programming skills in C++ and Python.
Experience with machine learning frameworks, especially PyTorch.
Strong understanding of robot learning principles and algorithms.
Experience with simulation environments (e.g. Isaac Lab, Isaac Sim)
Hands on experience of real robot testing.
Familiar with robotics middleware.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Ways to Stand out from The Crowd:
Real-world experience with humanoid robots, particularly in loco-manipulation tasks.
Experience with NVIDIA's Isaac platform and tools.
Hands-on experience with real-world robotic systems and hardware.
Contributions to open-source projects in the robotics or machine learning community.
Experience withvision-language-action(VLA) models.
Strong publication record in top-tier conferences and journals.
You will also be eligible for equity and .
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