Software Engineer, Machine Learning, Edge Tensor Processing Unit

1 Month ago • 2-4 Years • Artificial Intelligence

Job Summary

Job Description

This Software Engineer role focuses on training and optimizing machine learning models for the Tensor Processing Unit (TPU), specifically for edge devices. Responsibilities include developing and training edge-optimized models for various applications (computer vision, natural language processing, speech). The role also involves co-developing model optimization tools and infrastructure, customizing neural network architectures, building efficient ML training pipelines, and creating profiling/visualization tools. Collaboration with researchers and application developers is key. The position requires expertise in machine learning, model optimization, and experience with deep learning frameworks.
Must have:
  • Develop and train edge optimized models
  • Co-develop model optimization tools
  • Work with researchers and developers
  • Build efficient ML training pipelines
  • C++/Python & Data Structures/Algorithms experience
  • 2+ years ML model development experience
Good to have:
  • Master's/PhD in CS with ML focus
  • Experience with TensorFlow, PyTorch, or JAX
  • Publications or research in deep learning
  • 4+ years ML model development experience

Job Details

Minimum qualifications:

  • Bachelor’s degree in Computer Science or related technical fields, or equivalent practical experience.
  • 2 years of experience with software development in C++/python, and with data structures/algorithms.
  • 2 years of experience in developing and training machine learning models.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field with an emphasis on Machine Learning/Artificial Intelligence.
  • 4 years of experience in developing and training machine learning models.
  • Experience in publications or research related to deep learning.
  • Experience working with any deep learning frameworks, Tensorflow, Pytorch or JAX.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As a Software Engineer you will work on training and optimizing machine learning models for the Tensor Processing Unit (TPU). By working on enabling different models spanning varied applications (camera, Speech, Translate, TTS, etc.) on Edge TPU, you will gain exposure and expertise in the exciting direction of efficient model architectures, optimization methods and on-device machine learning activities at Google. Along with your technical expertise, you will manage project priorities, deadlines and deliverables.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

Responsibilities

  • Work on developing and training edge optimized models for genAI, computer vision, natural language and speech use cases.
  • Co-develop model optimization tools and infrastructure modules needed for automating customization and training of neural networks and architecture design space exploration.
  • Work with researchers and application developers to customize neural network architectures.
  • Write modular and efficient Machine Learning (ML) training pipelines and assist in building profiling and visualization tools.

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