2 days ago
Sunnyvale, CA, USAMid Level
H1B sponsor
Base Salary
$180k - $240k/yr
Responsibilities
- Implement and deploy learning-based manipulation policies for reliable real-world performance on physical robotic hardware.
- Adapt policies for new tasks and hardware using RL fine-tuning, policy distillation, and interactive imitation learning such as DAgger.
- Build and maintain teleoperation and demonstration-data pipelines, including retargeting, dataset aggregation, and curation.
- Drive policy development from simulation and offline evaluation through robust deployment and fine-tuning on robots.
- Develop low-latency visuomotor policies for grasping, in-hand manipulation, and whole-arm manipulation.
- Define evaluation metrics and regression tests for policy performance in simulation and on hardware.
- Collaborate with simulation, data, hardware, and systems teams to diagnose system-level issues.
- Maintain code quality through testing, documentation, and peer code reviews.
Requirements
- Strong experience in robotic manipulation, including grasping, in-hand or whole-arm control, high-DOF motion, and hardware deployment.
- Hands-on experience training and debugging learned policies using post-training, RL fine-tuning, distillation, and imitation learning methods such as DAgger.
- Proficiency in Python, C++, and PyTorch or JAX, with experience building real-time robotic software stacks.
- Experience with demonstration and teleoperation data and with building evaluation pipelines for learned policies.
- An MS with 3+ years of relevant experience or a recent PhD in Robotics, Computer Science, Electrical Engineering, or a related field.
- Relevant experience focused on learning-based manipulation or a closely related area, with a record of deploying learned policies on physical hardware.
- Preferred experience with IsaacSim, MuJoCo, or Drake; generalist manipulation policies; VR or haptic interfaces; retargeting algorithms; tactile or haptic feedback; 6D pose estimation; point cloud processing; or visual servoing.
Benefits
- Direct-hire position with an annual salary range of $180,000-$240,000.
- Physical requirements include desk and computer work, occasional lifting of up to 15 pounds, and sufficient vision, hearing, and speech for job duties.
Categories
ML EngineeringRobotics
About Apptronik
Apptronik designs and manufactures AI-enabled humanoid robots, led by its Apollo platform, to automate tasks alongside people in manufacturing and logistics, with potential use in healthcare and homes. The privately held company is headquartered in Austin, Texas, and grew out of the University of Texas at Austin’s Human Centered Robotics Lab; its team previously worked on NASA’s Valkyrie robot. Apptronik’s business model centers on selling robots and the software and services needed to deploy them in industrial environments.