Machine Learning Engineer - MLA Perception Offline Driving Intelligence
Develop and fine-tune multimodal large language models for offline analysis to enhance robotaxi environmental understanding and integrate into production for safe autonomous navigation. Requires MS/PhD in CS/ML, experience with LLMs, PyTorch, and large-scale data training.
Responsibilities
- Develop multimodal large language models that enhance our robotaxis' understanding of complex urban environments
- Implement model architectures and sophisticated training techniques
- Build large high quality datasets leveraging all the inputs from our sensor stack and the overall large scale data we have at Zoox.
- 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, safety, 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 large language models (LLMs)
- Experience building and maintaining ML training pipelines, including data preprocessing, model training, and evaluation
- Proficiency in Python and ML libraries (PyTorch, NumPy) demonstrated through professional or research projects
- Experience training models with large scale data
Bonus Qualifications
- Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
- Experience with autonomous robotics systems
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