Machine Learning Researcher (Humanoid Robots)

About Us Our vision is clear: to engineer and innovate robotics that not only enhance but redefine dexterity.

As a Robotics Scientist within our ranks, you'll be tapping into the most cutting-edge methods, developing training systems, and implementing algorithms that bring robotic manipulation into the realm of art.

The Role: In your role as an ML Scientist, Robotic Manipulation, you'll craft the future with your expertise.

Your day-to-day will be a blend of pioneering research and hands-on implementation.

You'll not only develop the algorithms that power our robots but also oversee their performance in simulations and guide them through their paces in the real world.

Responsibilities: Design and improve upon state-of-the-art Reinforcement Learning (RL) and Imitation Learning (IL) algorithms for practical robotic applications.

Keep pace with the frontier of RL/IL research, especially as it applies to robotics.

Spearhead research initiatives that promise transformative advancements in ML and robotics.

Enhance RL/IL learning processes with an eye on metrics that matter: sample efficiency, speed, and scalability.

Architect RL/IL training and data collection systems that seamlessly transition from digital to physical realms.

Experience and Expertise: Your path to becoming an ML Scientist has been rigorous: A Ph.D.

in a field that’s at the heart of our work, like Machine Learning, Computer Science, or Applied Mathematics.

A minimum of 5 years in the trenches of robotic manipulation, both in digital simulations and with robots that exist in the steel and circuits of our reality.

Hands-on practice in applying RL/IL methods with a particular focus on the tangible challenges of real-world robotics.

4 years of developing large-batch, parallel simulations for RL, proving your mettle in the virtual proving grounds of AI.

Demonstrated success in continual learning and sim-to-real transfers that polish our robotic prowess to perfection.

Skills: Proficient in Python 3.8+, PyTorch, TensorFlow, and ROS2.

Solid experience with Atlassian suite or equivalent tools like GitLab.

Traits: A relentlessly positive attitude, tempered with the patience and attention to detail required for solving complex problems.

Strong leadership capabilities, guiding R&D efforts with clarity and purpose.

A zeal for tackling new challenges, paired with an unwavering tenacity.

The enthusiasm to imbue machines with a touch of human-like intelligence.

The skill to shepherd new functionalities from the drawing board to deployment.

Keywords: Dexterous Manipulation, Robotic Manipulation, Reinforcement Learning, Imitation Learning, Robotics, Machine Learning, Python, PyTorch, TensorFlow, ROS2, Algorithm Development, Sim-to-Real, Continual Learning, Large-Batch Simulations.