MS/PhD Software Engineer: ML Frameworks & Efficiency Intern

First Roles

Mountain View (CA)

Híbrido

USD 80.000 - 113.000

Jornada completa

14 días+

Consigue una respuesta de este empleador

Tu currículum y tu carta de presentación, adaptados exactamente a lo que buscan contratar.

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Ventajas ofrecidas por este puesto de trabajo

Free breakfast
Free lunch
Free dinner
Free snacks
Onsite shuttle
Onsite gym
Housing/relocation bonus
Medical insurance
Dental insurance
Vision insurance
Intern networking events

Descripción de la vacante

Waymo is offering a Summer Intern position in Mountain View for MS/PhD students focused on Software Engineering, ML frameworks, and efficiency. You will work with the SIML team to scale ML capabilities, build reliable infrastructure, and enable rapid innovation for the Waymo Driver platform.

The role emphasizes hands-on ML, deep learning, and reinforcement learning, with hybrid onsite work and competitive intern benefits.

Formación

  • Pursuing an MS or PhD in a technical field with strong ML background.
  • Strong Python software development skills.
  • Experience with RL, ML frameworks and research mindset.

Responsabilidades

  • Understand the problem the current LPM model is trying to solve.
  • Improve/extend the RL infrastructure to support LPM model training needs.
  • Profiling and understanding slowness, maintaining and improving training efficiency.
  • Identify promising new RL technologies and integrate into our infrastructure.

Conocimientos

Python
ML
Reinforcement learning
JAX/Flax
PyTorch
TensorFlow

Educación

MS/PhD candidate in CS/EE/ML
PhD candidate in CS/EE/ML/Robotics

Herramientas

JAX
Flax
PyTorch
TensorFlow

Descripción del empleo

Waymo is offering a Summer Intern position in Mountain View for MS/PhD students focused on Software Engineering, ML frameworks, and efficiency. You will work with the SIML team to scale ML capabilities, build reliable infrastructure, and enable rapid innovation for the Waymo Driver platform.

The role emphasizes hands-on ML, deep learning, and reinforcement learning, with hybrid onsite work and competitive intern benefits.

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