Senior/Staff Machine Learning Engineer - Perception Offline Driving Intelligence
Job Summary
Job Description
The Offline Driving Intelligence (ODIN) team at Zoox is seeking a Senior/Staff Machine Learning Engineer to develop advanced multimodal large language models for environmental understanding in self-driving robotaxis. The role involves crafting algorithms that understand the world, devising paths of impact for autonomous navigation, and fine-tuning models for off-vehicle analysis. Responsibilities include leading LLM development, designing model architectures and training techniques using sensor data and large-scale datasets, driving end-to-end ML solutions from research to production, collaborating with cross-functional teams, and validating solutions with real-world driving scenarios. This position directly impacts the safety, productivity, and capability of Zoox's autonomous system.
Must have:
- 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
- Proficiency in Python and ML libraries (PyTorch, NumPy)
- Experience training with large scale datasets
Good to have:
- Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
- Experience with autonomous robotics systems
6 skills required
Job Details
The Offline Driving Intelligence (ODIN) team at Zoox is leveraging the latest in AI to craft algorithms that understand the world. We leverage large models first offline and we devise a path of impact into our self-driving robot, enabling safe and efficient navigation in complex environments.
As an engineer in the ODIN team, you will develop advanced multimodal large language models that enhance environmental understanding. You'll develop and fine-tune these models for off-vehicle analysis while working with the onboard team to deliver impact in 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 productivity, safety and the 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 effective model architectures and sophisticated training techniques, 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 with large scale datasets (e.g. tens of millions of videos)
Bonus Qualifications:
- Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
- Experience with autonomous robotics systems
$230,000 - $332,000 a year
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About The Company
Zoox is transforming mobility-as-a-service by developing a fully autonomous, purpose-built fleet designed for AI to drive and humans to enjoy.
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