
Applied Machine Learning Engineer, II - GPU Optimization
- Ann Arbor, MI
- $103,700-124,400 per year
- Permanent
- Full-time
Torc's virtual driver software utilizes cutting-edge deep learning techniques to perceive the vehicle's environment, predict the movements of other vehicles, and execute accurate driving decisions. We are actively seeking an engineer to join our hardware acceleration team, with a focus on the optimization of advanced deep learning models used by our virtual driver software (i.e. the “brain” of our autonomous truck). This is an exceptional opportunity for you to have a significant impact on the future of the autonomous vehicle industry by enhancing AI performance. We're on the road today, come help us drive the future of freight.What you'll do:
- Be a part of the team bringing L4 autonomous semi-trucks to market
- Work on the cutting edge of autonomy, optimizing deep learning models for execution on embedded NVIDIA GPUs
- Develop custom CUDA kernels and TensorRT plugins for perception and planning algorithms
- Collaborate with domain experts across the autonomy stack, influencing development, and helping deploy models to truck
- Identify and work to reduce system performance bottlenecks
- Be a good citizen of the engineering community, documenting work, reviewing code, participating in strategic discussions, etc.…
- Relevant bachelor's degree with 5+ years of professional experience, or advanced degree
- Proficiency with C++14, and the ability to write robust, efficient, and clean code
- Experience with CUDA programming and parallelization of algorithms
- Experience writing TensorRT plugins
- Comfortable using collaborative development tools such as Git and Jira
- Strong written and verbal technical communication skills
- Positive, team player mindset
- Autonomy or robotics experience
- Safety critical system development
- Experience with deep learning frameworks such as PyTorch or TensorFlow