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Machine Learning Engineer - Perception Offline Driving Intelligencejobs.frontdoordefense.com - Jobboard • San Francisco, California, United States
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Machine Learning Engineer - Perception Offline Driving Intelligence

jobs.frontdoordefense.com - Jobboard
  • US
    San Francisco, California, United States
  • US
    San Francisco, California, United States
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Über

Machine Learning Engineer - Perception Offline Driving Intelligence Develop multimodal large language models to improve autonomous vehicle hazard detection Location: San Francisco Bay Area
Compensation: $180,000 - 256,000 USD / year
Job Tags: Software
About The Role 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:
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
$180,000 - $256,000 a year
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign‑on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long‑term care insurance, long‑term and short‑term disability insurance, and life insurance.
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  • San Francisco, California, United States

Sprachkenntnisse

  • English
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