Senior Machine Learning Engineer

What you'll do

• Research and build multimodal, reinforcement-learning, and world-model systems for trajectory planning and vehicle actuation.
• Optimize and deploy models on vehicle edge hardware, profiling inference pipelines and reducing latency and resource bottlenecks.
• Build data pipelines to identify rare driving scenarios and use them to improve models and simulation testing.

What they ask for

• 4+ years of non-internship professional MLE experience.
• Expertise applying AI Transformers to robotics, physical actuation, or spatial-temporal data, with experience designing or training multimodal systems, VLA models, or generative Diffusion models.
• Experience with sensor fusion using Cameras, LiDAR, and Radar.
• Fluency in PyTorch or JAX and proficiency in Python; C++ familiarity or skills are also requested.

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

$208,000 - $263,500 USD base salary

Tools

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

AI focus

Physical AI for autonomous transport, including multimodal perception and actuation, reinforcement learning, trajectory planning, world models, post-training optimization, and data-driven improvement of autonomous driving models.