Robotics Learning Engineer

Sunnyvalefull time

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On Site

mid

$170k–$400k

H1B: no

Undercontrolroboticsinc Robotics Learning Engineer responsible for developing machine learning and AI systems for multipurpose humanoid robots. This includes designing learning algorithms for locomotion, perception, and motion planning.

Responsibilities

Create and optimize learning pipelines for training locomotion policies that generalize across environments
Develop and implement machine learning models for robot perception, decision-making, and motion planning
Create and optimize computer vision systems for environmental awareness and object recognition
Collaborate with the hardware team to integrate learning systems with the physical platforms
Design simulation environments for training and testing learning algorithms
Collect, process, and analyze field data to improve learning systems continuously
Develop metrics and benchmarks to evaluate robot learning performance
Stay current with the latest research and innovations in robotics and machine learning

Qualification

Master's or PhD in RoboticsStrong programming skills in PythonExperience with reinforcement learning

Required

Master's or PhD in Robotics, Computer Science, Machine Learning, or related field
3+ years of experience developing machine learning applications for robotics systems
Strong programming skills in Python, C++, and relevant ML frameworks (TensorFlow, PyTorch)
Experience with reinforcement learning, computer vision, and motion planning algorithms
Familiarity with ROS (Robot Operating System) or similar robotics frameworks
Knowledge of control systems and robot kinematics
Strong mathematical background in linear algebra, calculus, and statistics
Experience with simulation tools for robotics (Gazebo, MuJoCo, Isaac Sim, etc.)
Proven track record of implementing ML solutions in robotics applications
Experience with legged robot locomotion and dynamic stability control

Preferred

Experience with humanoid robots or complex multi-joint robotic systems
Knowledge of model predictive control (MPC) for locomotion
Familiarity with trajectory optimization for legged robots
Knowledge of industrial environments (construction, energy, mining, or manufacturing)
Understanding of safety considerations for learning-based robotic systems
Experience with edge computing and deploying ML models on embedded systems
Familiarity with human-robot interaction paradigms
Background in imitation learning or learning from demonstration

Benefits

Vision
Equity/RSU

Company

Undercontrolroboticsinc

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Source: greenhouse

Active within the past hour

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