Unknown Company

Staff Machine Learning Engineer, Multi-Modal Perception

san francisco, ca • Posted 6 days ago
Hybrid Full Time Electrical & Energy Engineering

Requirements

  • Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning experience
  • 5+ years experience in Machine Learning and Computer Vision
  • Experience with Python
  • Experience with ML frameworks like PyTorch or JAX
  • (Desirable) MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline
  • (Desirable) Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
  • (Desirable) Experience with C++

What the job involves

  • The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the autonomously driving vehicle (ADV), i.e., the system that “perceives” the world around the car
  • We work jointly with downstream teams on the optimization and integration into the Waymo Driver
  • We conduct our own research to address real-world problems and collaborate with research teams at Alphabet
  • We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware
  • In this hybrid role you will report to a Technical Lead Manager
  • Own tasks in the ML Driver, take responsibility for task scaling and task performance, create ML methods and recipes to scale and improve tasks
  • Analyze behavior of ML systems in real-world application, identify issues and root causes, advise or develop short- and long-term solutions
  • Monitor ML systems in production, develop methods for automatically detecting issues or regressions, develop AI-aided analysis and debugging tooling
  • Develop and maintain metrics for ADV relevant issues, including safety-critical and longtail issues

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