Software Engineer III, Machine Learning Services

1 Month ago • 3-5 Years • Artificial Intelligence

Job Summary

Job Description

This Software Engineer III role at Google focuses on optimizing and evolving machine learning infrastructure for Android devices. Responsibilities include enhancing performance, reliability, and efficiency of on-device machine learning and generative AI. You'll collaborate on new APIs for on-device ML, integrate infrastructure into Android apps and services, and work with external developers and hardware vendors. The role demands staying current with on-device ML and GenAI advancements, including multi-modal learning and expanding device compatibility. The ideal candidate will have experience with Java, C++, and ideally Python, along with a strong understanding of machine learning concepts and large language models.
Must have:
  • Bachelor's degree or equivalent experience
  • 2+ years software development experience
  • 1+ year Java development experience
  • 1+ year C++ development experience
  • Experience with AI/ML
  • Optimize ML infrastructure for Android
Good to have:
  • Experience with LLMs
  • Gradle experience
  • Release engineering experience
  • Python coding skills

Job Details

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience in software development.
  • 1 year of experience with software development in Java.
  • 1 year of experience with software development in C++ programming language.
  • Experience in Artificial Intelligence or Machine Learning.

Preferred qualifications:

  • Experience with machine learning or artificial intelligence concepts or technology.
  • Experience with Large Language Model.
  • Experience with Gradle.
  • Experience in release engineering.
  • Knowledge of coding with Python.

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.

Our infrastructure is used by tens of thousands of apps with billions of users, and executes trillions of machine learning inferences every day. On-device generative AI with Pixel first, then Samsung, and now other Original Equipment Manufacturers (OEMs).

In this role, you will work on infrastructure for machine learning on mobile devices.

Android is Google’s open-source mobile operating system powering more than 3 billion devices worldwide. Android is about bringing computing to everyone in the world. We believe computing is a super power for good, enabling access to information, economic opportunity, productivity, connectivity between friends and family and more. We think everyone in the world should have access to the best computing has to offer. We provide the platform for original equipment manufacturers (OEMs) and developers to build compelling computing devices (smartphones, tablets, TVs, wearables, etc) that run the best apps/services for everyone in the world.

Responsibilities

  • Optimize and evolve Google's infrastructure for machine learning and generative AI to ensure performance, reliability, and efficiency on Android devices.
  • Collaborate on the development and rollout of new Application Programming Interface (APIs) that expand the capabilities of on-device machine learning unlock novel use cases.
  • Work closely with internal teams across Google to integrate this infrastructure into critical Android applications and services.
  • Contribute to the broader Android Machine Learning ecosystem by partnering with external developers and hardware vendors.
  • Stay ahead of the curve in the evolving fields of on-device Machine Learning and GenAI, including areas like multi-modal learning and expanding device compatibility.

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