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Senior Staff Machine Learning Engineer - Perception

Leads development of ML algorithms for robot perception, including scene understanding, tracking, segmentation, and multi-modal foundation models using sensor data. Requires deep expertise in deep learning, computer vision, and production ML pipelines, collaborating across autonomy teams.

About the job

Responsibilities

  • Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time
  • Build multi-modal foundation models for on-vehicle and offline applications
  • Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems
  • Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field
  • Provide technical mentorship to the broader group of ML developers
  • Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments

Qualifications

  • BS, MS, or PhD degree in computer science or related field
  • Experience with training and deploying Deep Learning models on sensor data
  • Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines
  • Experience with modern computer vision techniques
  • Strong mathematical skills and understanding of probabilistic techniques
  • Fluency in C++ or Fluency in Python with a basic understanding of C++
  • Extensive experience with programming and algorithm design
  • Strong mathematics skills

Bonus Qualifications

  • Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
  • Experience with autonomous robots
  • Experience with realtime sensor fusion (e.g. LiDAR, camera, radar)
  • Experience with novel pipelines and architectures for convolutional neural nets
  • Experience with 3D data and representations (pointclouds, meshes, etc.)

Skills

Deep Learning, Computer Vision, Python, C++, Machine Learning Pipelines, PyTorch, TensorFlow, Lidar, Sensor Fusion, Point Clouds, Generative AI, Convolutional Neural Networks

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