Robotics Engineer

Build the Future of Humanoid Robotics

At gephr Labs, we're not just building robots—we're democratizing humanoid robotics for the entire world. We're looking for a talented  Robotics Engineer  to join our mission of making humanoid robot development accessible to everyone through our open-source humanoid training platform.

The Opportunity

You'll be at the forefront of humanoid robotics, contributing to gephr's open-source humanoid training platform that's changing how the world trains and deploys humanoid robots. This isn't just another engineering role; it's a chance to shape technology that thousands of developers, researchers, and companies will build upon.

What makes this role special :

• Your code will be public, impactful, and used by the global robotics community
• Collaborate with an open-source community of brilliant minds
• Help define the standards for the next generation of humanoid platforms

What You'll Do

Core Responsibilities :

Design and implement control systems for humanoid locomotion, manipulation, and balance

Develop and optimize training pipelines for humanoid behaviours using VLAs, RL and imitation learning

Build robust simulation environments and sim-to-real transfer workflows

Contribute to the core gephr platform architecture—kinematics, dynamics, perception, and control

Create comprehensive documentation, tutorials, and examples for the open-source community

Collaborate with external contributors and maintain high code quality standards

Debug and solve complex robotics challenges in both simulation and hardware

Push the boundaries of what's possible with accessible humanoid robotics

What We're Looking For

Required :

Bachelor's or Master's in Robotics, Computer Science, Mechatronics or related field

2+ years of hands-on experience in robotics (manipulation, locomotion, or mobile robotics)

Strong programming skills in Python and C++

Experience with robotics frameworks (ROS / ROS2, MuJoCo, PyBullet, Isaac, or similar)

Solid understanding of kinematics, dynamics, and control theory

Comfort working with Linux and command-line tools

Passion for open source and collaborative development

Bonus Points :

Experience with VLA models, reinforcement learning and imitation learning

Familiarity with humanoid robots or legged locomotion

Active GitHub profile with robotics projects

Experience with sim-to-real transfer and hardware integration

Knowledge of computer vision and sensor fusion

Contributions to open-source robotics projects

Experience with modern ML frameworks (PyTorch, JAX, TensorFlow)

Why Gephr Labs?

Impact :  Your work will be used by researchers, hobbyists, and companies worldwide. Every commit you make helps democratize advanced robotics.

Open Source First :  We believe the future of robotics is open. Full transparency, community-driven development, and standing on the shoulders of giants.

Learning Culture :  Work with cutting-edge technology daily. We encourage experimentation, rapid iteration, and learning from failures.

Flexibility :  We trust you to do great work. Remote-friendly with flexible hours because great engineering doesn't happen on a fixed schedule.

Community :  Join a passionate community of robotics enthusiasts who contribute, collaborate, and push each other to build amazing things.

The Stack

Languages :  Python, C++, CUDA

Frameworks :  ROS2, PyTorch, MuJoCo, NVIDIA Isaac

Tools :  Git, Docker, CI / CD pipelines

Hardware :  Real humanoid platforms

How to Apply

Send us :

Your resume

Your GitHub profile (we want to see your code!)

A brief note about :

A robotics problem you're proud of solving

Why you're excited about open-source humanoid robotics

What you'd contribute to the gephr humanoid training platform

Think you're a fit but don't check every box?  Apply anyway. We value passion, curiosity, and the drive to learn just as much as experience.

Start contributing to the gephr humanoid training platform and we'll know this is your calling : https : / / github.com / manoj92 / gephr

Apply at careers@gephr.com or via LinkedIn.

"The future of robotics won't be built behind closed doors—it'll be built in the open, together."