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.
277k – 389k
HybridML Engineering
About the role
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 LearningComputer VisionPythonC++Machine Learning PipelinesPyTorchTensorFlowLidarSensor FusionPoint CloudsGenerative AIConvolutional Neural Networks
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277k – 407k
HybridML Engineering
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