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Zoox

Senior/Staff Machine Learning Engineer - Perception Offline Driving Intelligence

Reposted 2 Days Ago
Be an Early Applicant
Hybrid
Foster City, CA
242K-333K Annually
Senior level
Hybrid
Foster City, CA
242K-333K Annually
Senior level
Develop advanced multimodal large language models for autonomous driving, optimize solutions using real-world scenarios, and collaborate with engineering teams.
The summary above was generated by AI
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

About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

Top Skills

Ml Libraries
Numpy
Python
PyTorch
HQ

Zoox Foster City, California, USA Office

4000 E 3rd Ave, Foster City, CA, United States, 94404

Zoox Foster City, California, USA Office

1149 Chess Drive, Foster City, CA, United States, 94404

Zoox Fremont, California, USA Office

47540 Kato Road, Fremont, CA, United States, 94538

Zoox San Francisco, California, USA Office

60 Broadway St, San Francisco, CA, United States, 94111

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