PhD AI/ML Software Engineer - Research to Production

Google; Kirkland (WA); On-site; USD 147,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) with company match

Paid time off

Sick time

Parental leave

Holidays

Job summary

Google's engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our PhD Software Engineer role focuses on ML/AI systems spanning research to production across AI & Infrastructure, Cloud, YouTube, Search, Ads and more!

As a PhD graduate, your research will guide cutting-edge ML solutions. You will collaborate with teams, tackle challenging problems, and contribute to scalable ML systems and APIs in a

Qualifications

• PhD in Computer Science, AI, or related field or equivalent practical experience.
• Experience coding in Python, C, C++, Java, JavaScript or Golang.
• Experience in Machine Learning or Artificial Intelligence.

Responsibilities

• Collaborate or lead on team projects to design, analyze, and develop advanced ML systems across the stack.
• Support building end-to-end ML systems spanning hardware to production APIs.
• Optimize complex system performance, memory usage, and production reliability.
• Promote high-quality engineering practices through code reviews and testing.

Skills

PhD in CS/AI

Python

C

C++

Java

JavaScript

Golang

Machine Learning

Education

PhD in CS/AI or related field

Tools

PyTorch

JAX

TensorFlow

Rust

Job description

Google's engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our PhD Software Engineer role focuses on ML/AI systems spanning research to production across AI & Infrastructure, Cloud, YouTube, Search, Ads and more!

As a PhD graduate, your research will guide cutting-edge ML solutions. You will collaborate with teams, tackle challenging problems, and contribute to scalable ML systems and APIs in a