Senior Machine Learning Engineer, Perception & Embodied AI

What you'll do

• Own the end-to-end lifecycle for safety-critical ML perception models including design, training, validation, and deployment.
• Develop deep learning models for 3D object detection, tracking, and real-time map detection of the drivable world.
• Implement multi-modal sensor fusion using camera, LiDAR, and radar data to improve environmental awareness.
• Build and scale ML training infrastructure including data mining, loading, and multi-stage evaluation pipelines.
• Optimize model performance for low-latency execution on resource-constrained vehicle embedded hardware.
• Conduct data-driven analysis to debug and resolve failures in long-tail and adversarial scenarios.
• Define and implement robust metrics to guide the development of perception models.
• Integrate perception outputs with safety and systems engineering functions.

What we're looking for

• BS, MS, or PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field.
• 5+ years of professional experience in Computer Vision, Deep Learning, and Perception in a production environment.
• Hands-on experience with modern deep learning frameworks like PyTorch or TensorFlow for training and debugging complex DNNs.
• Experience fusing data from multiple sensor modalities including Camera, LiDAR, and/or Radar.
• Practical experience deploying and optimizing ML models for resource-constrained, real-time embedded systems.
• Ability to drive model improvements through large-scale data analysis, error logging, and data curation.
• Expertise with Transformer-based models for 3D detection, tracking, and scene understanding is a bonus.
• Technical leadership experience including mentoring junior engineers and leading feature development from concept to launch.