Machine Learning Engineer - Robot Perception

Qualifications

• Must-have:
• MS or PhD in machine learning, computer science, robotics, or a related field.
• Strong background in computer vision, deep learning, and sensor fusion.
• Proficiency in Python and C++, with experience in frameworks like PyTorch, TensorFlow, OpenCV, and ROS.
• Hands-on experience with real-world robotics perception systems (e.g., SLAM, 3D reconstruction, multimodal perception).
• Experience working with hardware, including setting up and calibrating cameras, LiDAR, and other sensors.
• Experience with data collection, preprocessing, and management in the context of training ML models.
• Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
• Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.
• Nice-to-have:
• Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
• Experience in: Developing models that can handle noisy, incomplete, or sparse data. Deployment of ML models to edge devices for real-time inference (e.g., NVIDIA Jetson). Accelerating ML training processes using GPU, TPU, or other HW accelerators. General knowledge of robotics principles, including kinematics, dynamics, and control.
• Developing models that can handle noisy, incomplete, or sparse data.
• Deployment of ML models to edge devices for real-time inference (e.g., NVIDIA Jetson).
• Accelerating ML training processes using GPU, TPU, or other HW accelerators.
• General knowledge of robotics principles, including kinematics, dynamics, and control.