Robotics Engineer - Navigation focus

About the Role:

We are looking for strong candidates who have a background in robotics and machine learning, especially with experience in SLAM, robot navigation (classical or learning-based), and geometric foundation models (e.g. VGGT, MapAnything, etc). You will work across research and engineering, from defining research problems and developing new methods to training, simulation, evaluation, and deployment-oriented experimentation.

Responsibilities

• Develop new methods and systems that advance the state of the art in robotics, 3D perception, navigation, and foundation models.

• Adapt standard machine learning models and frameworks to robotics applications (e.g. computer vision, SLAM, navigation).

• Build efficient robotics pipelines integrating sensor fusion, perception models, geometric reasoning, and model inference.

• Define research goals informed by practical engineering concerns.

• Design high fidelity simulation environments that advance sim-to-real transfer and enable faster iteration cycles for deploying new robots.

• Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results.

• Partner with customers to deploy robots with navigation capabilities in real production environments.

• Contribute to publications and open-sourcing efforts.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

• Research experience in machine learning, robotics, and computer vision.

• Experience with developing robotics algorithms or machine learning models at scale.

• Programming experience in Python/C++. Good understanding of deep learning frameworks like Pytorch or Jax.

• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Desired Qualifications

• Master's/PhD in Robotics, Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

• Direct experience in robotics, computer vision, or machine learning research.

• First author publications at peer-reviewed AI and robotics conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICRA, IROS, CORL).

• Experience with high fidelity simulation platforms such as AirSim, CARLA, Isaac Sim, Mujoco, Maniskill among others.

• Experience building efficient robotics pipelines involving sensor fusion and model inference