Machine Learning Engineer

What you'll do

• Own the ML lifecycle, including data preparation, training, evaluation, deployment, and monitoring.
• Develop autonomous-driving models and optimize neural networks for constrained vehicle hardware and real-time inference.
• Build ML pipelines and evaluate model performance using simulation and real-world driving data; collaborate across autonomy, systems, hardware, and infrastructure teams.

What they ask for

• Strong Python skills and experience with PyTorch or TensorFlow.
• Strong C++ skills and experience integrating ML models into high-performance production systems.
• Deep understanding of ML workflows and experience deploying and optimizing neural networks for real-time, embedded, robotics, autonomous-driving, or other performance-constrained systems.
• Experience with model optimization techniques and software profiling, latency optimization, system-level debugging, and data-flow analysis.

Nice to have

• Experience with CUDA, TensorRT, and cloud-based ML pipelines, preferably Azure.
• Experience with advanced model types or safety-critical ML systems; publications or technical contributions in relevant areas are a plus.

Pay

$170,000 - $240,000 (base salary)

Tools

Python, PyTorch, TensorFlow, C++, CUDA, TensorRT, Azure

AI focus

Develop and optimize autonomous-driving ML models for perception, prediction, planning, and scene understanding, including efficient neural networks and real-time deployment on vehicle hardware.