jobapplier

Machine Learning MS/PhD Intern (Perception, Summer 2027)

Waymo

Skills

Required

  • ML
  • Robotics
  • JAX / PyTorch / Tensorflow

Preferred

  • machine learning
  • camera / radar / lidar / audio
  • object detection
  • segmentation
  • 3D object detection and tracking
  • open vocabulary detection
  • semantic segmentation
  • Python
  • CV research

Waymo, the leading self-driving technology company, as a Machine Learning MS/PhD Intern in the Perception team. This internship offers the opportunity to work on cutting-edge projects that have a significant impact on the company. You will design and implement state-of-the-art multi-modality perception models, train and evaluate ML models on vast driving data, and gain experience using large-scale ML infrastructure. The internship is based on-site at Waymo's headquarters in Mountain View, CA, and offers a range of benefits including medical, dental, and vision insurance, competitive compensation, and a hybrid work model.

Responsibilities

  • Train and evaluate machine learning models on vast and high fidelity data from Waymo driving logs, gaining experience using large scale ML infrastructure.
  • Collaborate with research teams at Alphabet to address real-world problems and optimize models for onboard and offboard hardware.

Requirements

  • Enrolled in a PhD program in Computer Science, Robotics, or a similar technical field of study or enrolled in a master's program with a strong publication record
  • Experience building ML models with JAX, PyTorch or Tensorflow

Preferred

  • Design and implement state-of-the-art multi-modality (camera/radar/lidar/audio) and multi-task perception models, focusing on areas such as 3D object detection and tracking, open vocabulary detection, and semantic segmentation.

Experience in Python

  • Strong track record of high quality ML / CV research. Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI
  • Experience in object detection, segmentation, multiple-object tracking audio perception or occupancy detection