Machine Learning Engineer II – Autonomous Driving, Inference Runtime
Job Description:
- Deploy and Optimize Machine Learning model architectures across May’s Autonomous Driving training and inference stacks.
- Own the model-compilation and deployment pipeline end-to-end.
- Establish and defend latency/throughput budgets across the AV stack, including profiling, regression and integrity tests.
Requirements:
- Bachelor’s or Master’s degree in Robotics, Computer Science, Computer Engineering, or a related field with strong mathematical and engineering foundations.
- A minimum of 2 years writing software to interface with GPU and ML systems.
- Proficiency in C/C++/CUDA/PyTorch and experience in Linux environments.
- Familiarity with basic Perception and Planning concepts in Autonomous Driving.
- Familiarity with NVIDIA compute architectures (Ada, Hopper, Blackwell, etc).
- Familiarity with common profiling tools such as Nsight, Pytorch Profiler, flamegraph.
- Understanding of Quantization (INT8/FP8/FP16) and other compression techniques.
- Familiarity with NVIDIA DRIVEOS architecture and SoCs (Orin/Thor).
- Familiarity with techniques for scaling training throughput (batching, FSDP, streaming dataloaders).
Benefits:
- Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate.
- Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.
- Rich retirement benefits, including an immediately vested employer safe harbor match.
- Generous paid parental leave as well as a phased return to work.
- Flexible vacation policy in addition to paid company holidays.
- Total Wellness Program providing numerous resources for overall wellbeing