Senior ML Systems Engineer, AICore

2 Days ago • 5-8 Years • Artificial Intelligence

Job Summary

Job Description

This Senior ML Systems Engineer role at Google's AICore in Taipei, Taiwan focuses on bringing Gemini to the Android ecosystem. Responsibilities include designing privacy-preserving, on-device ML systems; collaborating with Android partners to optimize Gemini models for various NPUs; developing algorithms and models to boost on-device Generative AI performance; and ensuring exceptional performance, reliability, and user delight through model optimization and quality assurance. The role requires strong software development skills, experience with ML models, and a deep understanding of software design and architecture. The successful candidate will partner with CoreML experts and contribute to shaping the future of mobile AI.
Must have:
  • 5+ years software development experience
  • 3+ years software product experience
  • Experience with ML models (DNN, LLM)
  • Familiarity with ML frameworks (PyTorch, TensorFlow)
  • Software design and architecture experience
Good to have:
  • Master's/PhD in CS
  • Technical leadership experience
  • Model optimization techniques (quantization, sparsity)

Job Details


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 1 year of experience in a technical leadership role.
  • Experience with Machine Learning models (e.g., DNN, LLM, etc.) training, data processing, and evaluation.
  • Familiarity with at one popular ML framework (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.

In this role, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices and 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 and Services team is making people's lives better through technology.

Responsibilities

  • Partner with CoreML experts to bring Gemini to the Android ecosystem to shape the future of mobile AI for billions.
  • Design privacy-preserving, on-device ML systems that fundamentally change mobile interaction and enhance core functionalities at massive scale.
  • Collaborate with Android partners to optimize and compress Gemini models (e.g., using techniques like quantization and sparsity) for peak performance on a wide array of Neural Processing Units (NPUs), achieving cross-ecosystem optimization.
  • Develop next-generation algorithms and models to dramatically boost the performance and efficiency of on-device Generative AI, and develop and enhance model fine-tuning pipelines to facilitate efficient and easy downstream feature development.
  • Deliver exceptional performance, reliability, and user delight through model optimization and quality assurance.

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