Machine Learning Engineer - Perception Semantics - Zoox

Job Title: Machine Learning Engineer - Perception Semantics
Job Location: Foster City, CA
Job Listing URL: https://jobs.lever.co/zoox/deaa9c24-daeb-461d-bcd3-2098bb3581f5
Job Description: The Perception team at Zoox is fundamental to our autonomous vehicle technology, creating the understanding of the world for our self-driving robots. We enable safe and efficient navigation in complex environments through sophisticated detection, classification, and tracking systems.
As an engineer in the Semantics and Foundation Model team, you will develop advanced multimodal large language models that enhance our vehicles' environmental understanding. You'll develop and fine-tune these models for off-vehicle analysis while also optimizing them for real-time performance on our robotaxi platform, ensuring they can efficiently identify hazards and interpret driving restrictions with minimal latency. Working alongside world-class engineers and researchers, you'll leverage premium sensor data and cutting-edge infrastructure to validate your algorithms in real-world conditions, directly impacting the safety and capability of Zoox's autonomous system.
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

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