Staff Machine Learning Engineer

What you'll do

• Develop multimodal models, world models, and reinforcement-learning or distillation methods for vehicle perception, planning, and actuation.
• Optimize and deploy models on vehicle edge hardware, profiling inference pipelines and reducing latency and resource bottlenecks.
• Build data pipelines to identify and curate rare driving scenarios and support simulation, testing, and model improvement.

What they ask for

• 10+ years of non-internship professional MLE experience.
• Deep expertise applying AI Transformers to robotics, physical actuation, or spatial-temporal data; experience with multimodal systems, VLA models, or generative Diffusion models.
• Experience with sensor fusion using Cameras, LiDAR, and Radar.
• Proficiency in Python and PyTorch or JAX; C++ is also required for some specializations.

Nice to have

• Experience with multi-task learning, Birds-Eye-View (BEV) frameworks, representation learning, or data tokenization.
• Familiarity with low-level camera/sensor interfaces and robotics hardware.

Pay

$273,000 - $345,000 per year (USD, base salary)

Tools

PyTorch, JAX, Python, C++, TensorRT, CUDA, Cameras, LiDAR

AI focus

Physical AI for autonomous transport, including multimodal perception and actuation, world models, reinforcement learning, model distillation and optimization, and data curation for long-tail driving scenarios.