Robotics Learning Engineer

About Noble Machines

Noble Machines (formerly Under Control Robotics) builds multipurpose robots to support human workers in the world's toughest jobs—turning dangerous work from a necessity into a choice. Our work demands reliability, robustness, and readiness for the unexpected—on time, every time. We're assembling a mission-driven team focused on delivering real impact in heavy industry, from construction and mining to energy. If you're driven to build rugged, reliable products that solve real-world problems, we'd love to talk.

Position Overview

At Noble Machines, building is a team sport. As a machine learning engineer, you'll take ownership and lead the development of advanced machine learning and AI systems powering multipurpose humanoid robots in the real world. You'll design, implement, and optimize learning algorithms that enable robots to move fluidly across diverse environments while performing complex manipulation tasks.

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

Requirements

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

Nice to Have

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

Experience with SLAM (Simultaneous Localization and Mapping) techniques

Publications in relevant conferences (ICRA, IROS, NeurIPS, etc.)

The base salary range for this full-time position is $170,000 - $400,000, in addition to bonus, equity and benefits.

To apply, submit your resume here or email [email protected] . To increase your chances of being selected for an interview, we encourage you to include up to TWO examples of your most representative work featuring hardware demonstrations.