Research Scientist - Reinforcement Learning in Cambridge

Energy Jobline ZR; Cambridge; On-site; GBP 80,000 - 100,000; Full time

Job summary

A global energy job board is seeking a Reinforcement Learning Research Scientist in Cambridge. The ideal candidate will have a strong background in robotics and experience in research and development, specifically in learning-based locomotion and ultra-mobile systems. The role demands advanced programming skills in Python or C++, with a focus on robotics applications. This position offers significant opportunities to contribute to cutting-edge technology in the field.

Qualifications

• Minimum 2 years, ideally 6+ years of experience in research and development.
• Proven track record in top-tier conferences in Machine Learning.
• Practical hardware experience is essential.

Responsibilities

• Research on learning-based locomotion and ultra-mobile systems.
• Develop technology for robots to advance their capabilities.
• Engage in robotics projects focusing on legged robots.

Skills

Technical proficiency in Reinforcement Learning

Advanced programming in Python

Experience with deep learning frameworks such as PyTorch

Experience with sim-to-real for robotic hardware

Expertise in perception-based control

Education

MS / PhD in robotics, computer science, or related fields

Tools

C++

ROS or ROS2

Docker

Job description

Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide.

We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.

Our Mission

Our mission is to solve the most important and fundamental challenges in AI and Robotics to enable future of intelligent machines that will help us all live better lives.

We aim to advance athletic intelligence to new heights by leveraging simulation-based methods like Reinforcement Learning, augmenting them with model information.

Reinforcement Learning Research Scientists

Will have proven hands-on research or industry experience focusing on one or more of these key areas: Learning-based locomotion, loco-manipulation, or ultra-mobile systems. Having practical hardware experience is essential for this role. If you are passionate about developing technology for robots and using it to advance their capabilities and usefulness, this team will be a great fit for you!

Senior Role Requirements

We are looking for experienced industry candidates. Ideally, looking for candidates who have experience working with Humanoids, Legged Robots, Quadrupedal, Locomotion and RL technology.

Requirements

• MS / PhD or equivalent industry experience in robotics, computer science, or related fields
• Minimum of 2 years exp. 6+ years of experience in research and development
• Ability to demonstrate technical proficiency in Reinforcement Learning, Control, Robotics, or Imitation Learning
• Experience with sim-to-real for robotic hardware specifically legged robots or highly dynamic mobile vehicles.
• Experience in working with perception-based control
• Advanced programming skills in Python or C++
• Expertise with deep learning frameworks such as PyTorch and robotic simulation
• Proven track record in top-tier conferences and journals in Machine Learning, Robotics, Control, or related fields

Bonus

• Knowledge of Model Predictive Control
• Experience in combining model-based and data-driven approaches
• Experience in working with Isaac-Gym, Isaac-Sim, or Orbit
• Experience in working with ROS or ROS2
• Experience with Docker, cloud computing, or similar applications
• Experience with parallel programming (e.g., CUDA)

These attributes are great to have but not required. Candidates who lack these should not be discouraged from applying.

We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to , , , , , , status, genetics, protected veteran status, , or expression, or any other characteristic protected by federal, state or local laws.

If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.