Machine Learning Engineer - Perception Semantics

In this role, you will:

• Lead the development of multimodal large language models that enhance our robotaxis' understanding of complex urban environments
• Design and implement efficient model architectures, balancing performance and computational constraints through fine-tuning and distillation techniques
• Drive end-to-end ML solutions from research to production, utilizing Zoox's extensive data pipelines and infrastructure to improve autonomous driving capabilities
• Collaborate with perception, planning, and systems teams to integrate your models into the vehicle's decision-making pipeline
• Validate and optimize your solutions using real-world driving scenarios, directly contributing to the safety and reliability of Zoox's autonomous system

Qualifications

• MS or PhD in Computer Science, Machine Learning, or related technical field
• Demonstrated experience training and deploying perception and computer vision based models
• Experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluationProficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
• Experience with model optimization techniques such as quantization, pruning, or knowledge distillation

Bonus Qualifications

• Proficiency in C++
• Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
• Experience with autonomous robotics systems