Research Engineer, Robotics

The Role
As a Research Engineer on the Robotics team, you will deploy and refine state-of-the-art AI models for mobile manipulation on real robots. This role exists to bridge the gap between cutting-edge research and real-world robotic applications, ensuring that Mistral’s in-house models are not only theoretically sound but also practical, scalable, and effective in dynamic environments.

You will join a team of engineers and researchers dedicated to pushing the boundaries of what robots can achieve. Your work will directly impact the development of autonomous systems, enabling them to operate reliably in complex, real-world scenarios. The scope of this role spans from architecting data pipelines for model training to maintaining fleets of diverse robots, all while collaborating closely with cross-functional teams to validate and iterate on robotic systems.

What You Will Do

• Deploy state-of-the-art AI models for mobile manipulation on real robots in production environments.

• Architect and optimize data pipelines to support the training of advanced robotics models on large-scale datasets.

• Set up, maintain, and scale fleets of robots, ensuring their operational readiness and reliability.

• Design and conduct experiments to validate robotic systems in real-world conditions.

• Collaborate with engineers and researchers to refine models and improve system performance.

• Hands-on experience developing software for real-world robotics applications.

• Mastery of Python and a strong background as a software developer.

• High engineering competence, with the ability to design complex systems and deploy them in production.

• A self-starter mindset, with the autonomy to drive projects forward and the adaptability to collaborate effectively.

• Experience with robotic control frameworks, such as ROS, and proficiency in sensor integration and actuator control.

• Knowledge of control theory, machine learning, or computer vision as applied to robotics.

• Experience with robotics simulators, hardware development, or maintaining large codebases.

• A proactive approach, with a focus on delivering results and continuously improving systems.