Google

Staff Software Engineer, On-Device Machine Learning Infrastructure

Google$207K — $301K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years in testing and launching software products, with 3 years in software design and architecture.
  • 5 years of experience in one or more areas such as Speech/audio technology, reinforcement learning, or ML infrastructure.
  • 5 years in ML design and ML infrastructure, covering model deployment and debugging.

Responsibilities

  • Create roadmaps for developer-facing APIs, SDKs, and tools to support LLM workflows.
  • Optimize Generative AI performance across diverse hardware environments.
  • Design resilient systems to anticipate scaling challenges as LLMs grow in complexity.
  • Coordinate cross-functional efforts to develop performance and evaluation workflows with multiple teams.
  • Provide technical mentorship and establish practices to enhance team productivity.

Benefits

  • Work within a team that influences critical technical decisions company-wide.
  • Opportunity to contribute to cutting-edge on-device ML deployment across various platforms.
  • Access to resources and collaboration with top-tier experts in their fields.
  • Partake in the innovation pace at one of the largest tech companies globally.
Full Job Description
Minimum qualifications:
  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  • 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:
  • Master's degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures and algorithms.
  • 3 years of experience working in a complex organization involving cross-functional, or cross-business projects.
  • Track record of leading and delivering ML projects focused on on-device deployment (e.g., Android, iOS, web browsers, or embedded devices).
  • Knowledge of ML converters/compilers and runtimes, and hardware-accelerated ML inference techniques.
  • Understanding of Generative AI model architectures and their optimization for on-device execution.


With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

In this role you will deliver on-device ML infrastructure with leading performance, enabling framework and device optionality at scale. You will enable on-device deployment of key models, such as Gemini Nano and Gemma, across various accelerators (e.g., GPU / Pixel TPU / NPUs / CPU) on Android, Chrome, and more.

The Core team builds the technical foundation behind Google's flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google's products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $301000 (USD) 20% bonus target equity benefits

Learn more about benefits at Google .

Responsibilities
  • Create roadmaps for developer-facing Application Programming Interfaces (APIs), Software Development Kits (SDKs), and tools, ensuring they meet the evolving needs of Large Language Models (LLMs) workflows.
  • Solve technically tests problems that exceed the scope of a generalist Software Engineers, specifically around optimizing Generative AI performance across heterogeneous hardware (CPUs, GPUs, and EdgeTPUs).
  • Guide the team in designing resilient and robust systems, proactively anticipating scaling bottlenecks or shifts in usage as LLMs become increasingly complex.
  • Coordinate efforts across multiple groups, including Android ML, ML Compiler, and DeepMind, to co-design performance and evaluation workflows.
  • Provide technical mentorship, and implement new practices that address team needs and increase the velocity of your teammates.


About Google

Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
Learn more about Google
Size
156,500 employees
Market Cap
$1,115.4 billion
Industry
Net Income
$40.2 billion
Founded
1998
5 Year Trend
+23.3%
Revenue
$182.5 billion
NASDAQ

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