📋 Description

• Architect scalable pipelines for generating synthetic and procedurally varied robotic interaction
• Build SOTA, scalable simulation environments developing task data generation, ML, and scene domain
• Define data-generation curricula that progress from constrained primitive actions to long-horizon
• Generate targeted recovery data for rare but safety-relevant conditions, including failed grasps
• Design systems for efficiently replaying, perturbing, relabeling, and extending real-world robot
• Establish provenance, metadata, versioning, and reproducibility standards for simulated datasets.

🎯 Requirements

• PhD or Master’s degree in Computer Science, robotics, machine learning, data science, electrical
• 9+ years of industry experience, post training, developing simulation, machine learning, robotics
• Proven hands-on experience with at least one major robotics simulation platform: NVIDIA Isaac Sim
• Expertise in creating custom simulation environments, robot assets, task definitions, sensors
• Expertise with Python and modern machine-learning frameworks such as PyTorch
• Experience working with robot kinematics, dynamics, coordinate frames, calibration, trajectory

🎁 Benefits

• Market-competitive compensation packages, inclusive of base pay, incentives, benefits, and equity.
• Equal Opportunity Employer
• Preference given to qualified candidates who do not reside in certain states (Alabama, Arkansas