Autonomy Engineer - Perception

About the Role

As an Autonomy Engineer - Perception at Tycho.AI, you will design, build, and validate perception systems for intelligent autonomous vehicles. You will collaborate with a cross-functional team of electrical, mechanical, and software experts to explore new concepts through rapid, iterative prototyping. We are seeking adaptable engineers who collaborate effectively across disciplines, brainstorm innovative ideas, and navigate through emerging embedded technologies. Most importantly, you should have a proven ability to drive a concept through the prototype phase and excel in hardware/software co-development.

Responsibilities

• Design, implement, and maintain autonomy software for computer vision and autonomy tasks, including scene reconstruction, object detection, and navigation.
• Integrate systems into real-world platforms, bridging research and production.
• Stay current on research and apply state-of-the-art techniques in autonomy and perception.

Requirements

• Master’s or PhD degree in Robotics, Engineering, Computer Science, or a related field; or equivalent working experience.
• Proficiency in C/C++ with experience shipping production-grade software.
• Experience building SLAM, perception, and sensor fusion systems.
• Strong foundation in both 2D (e.g., object detection, segmentation) and 3D (e.g., multi-view geometry, scene reconstruction) computer vision and perception tasks.
• Hands-on experience working with real sensor data, particularly in challenging environments, such as night, sea, or underground.
• Experience with recent developments in ML for computer vision, including ViT and other ML architectures for tasks like segmentation, object detection, classification etc.
• Comfortable developing and reasoning about multi-threaded real-time systems.

Nice to Have

• Experience working with embedded robotics platforms, such as NVIDIA Jetson.
• Experience optimizing and accelerating ML models for deployment, specifically using techniques like quantization, distillation, or architectural refinement.
• Familiarity with dense scene reconstruction, like occupancy grids, NeRF, or Gaussian splatting.
• Familiarity with perception model performance evaluation and evaluation pipelines.