The Feature Development team is seeking a Senior Embedded ML Engineer - Vision to develop, optimize, and deploy machine learning models for perception systems used in autonomous driving.
Requirements
- Expertise with Python and C++
- Proficiency in PyTorch, CUDA and TensorRT
- Strong foundation in computer vision and deep learning frameworks
- Experience deploying real-time models on embedded hardware (e.g., NVIDIA Jetson, Orin)
- Fundamentals of image signal processing
- Familiarity in synthetic data, augmentation, and handling edge cases in ML.
- Experience with sensor calibration.
Responsibilities
- Design and develop machine learning and computer vision algorithms for object detection, segmentation, tracking, and sensor fusion in autonomous driving.
- Deploy and optimize ML models on embedded systems, including GPUs and custom hardware accelerators (e.g., NVIDIA Jetson, Xavier, or equivalent).
- Profile and optimize ML pipelines for latency, memory usage, and power consumption in embedded environments.
- Conduct research and stay up to date with the latest advances in deep learning, computer vision, and embedded AI.
- Test and validate models in simulation and real-world autonomous driving scenarios.
- Participate in code reviews, architecture discussions, and system integration planning.
- Collaborate with hardware, software, and perception teams to align ML solutions with system constraints and real-time requirements.
Other
- Master’s in Computer Science, Electrical Engineering, or related field with 6+ years of AV related industry experience
- Collaborative skills and experience working across hardware, software, and autonomy functions in agile settings.
- Mentor junior engineers and contribute to technical leadership within the team.
- Familiarity with automotive or embedded safety standards (e.g., ISO 26262).
- PhD in Computer Vision, Imaging, AI, or related field.
