ML System Engineer, AICore

1 Day ago • 3-5 Years • Artificial Intelligence

Job Summary

Job Description

This ML System Engineer role at Google's AICore in Taipei, Taiwan, involves partnering with DeepMind and CoreML to integrate Gemini into the Android ecosystem. Responsibilities include designing privacy-preserving, on-device ML systems, collaborating with Android partners to optimize Gemini models for various NPUs, developing next-generation algorithms and models for on-device Generative AI, and ensuring excellent AI experiences through model optimization and quality assurance. The ideal candidate will have experience with software development (Python, C++), data structures, algorithms, and ML/Deep Learning frameworks (PyTorch, Jax, TensorFlow).
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development experience
  • 2+ years experience with data structures/algorithms
  • 1+ year experience with Machine Learning/Deep Learning
  • Experience with ML frameworks (PyTorch, Jax, TensorFlow)
Good to have:
  • Master's or PhD in CS
  • Technical leadership experience
  • Experience with ML model training, data processing, and evaluation

Job Details


Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 2 years of experience with software development in one or more programming languages (e.g., Python, C++), or 1 year of experience with an advanced degree.
  • 2 years of experience with data structures or algorithms.
  • 1 year of experience with Machine Learning, Deep Learning.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • 1 year of experience in a technical leadership role.
  • Experience with Machine Learning models, training, data processing and evaluation.
  • Experience with ML frameworks (e.g., PyTorch, Jax, TensorFlow).

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. Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Responsibilities

  • Partner with DeepMind and CoreML team to bring Gemini to the Android ecosystem to support the future of mobile AI for billions.
  • Design privacy-preserving, on-device ML systems that change mobile interaction and enhance core functionalities at scale.
  • Collaborate with Android partners to fine-tune Gemini models for excellent performance across an array of Neural Processing Units (NPUs) to achieve cross-ecosystem optimization.
  • Develop next-generation algorithms and models to enhance the performance and efficiency of on-device Generative AI.
  • Deliver excellent AI experiences to ensure exceptional performance, reliability, and user delight through model optimization and quality assurance.

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