Senior AI/ML Software Engineer – Equity Eligible

Google; San Jose (CA); On-site; USD 147,000 - 210,000; Full time

Job summary

Google is seeking software engineers in California to work on next-generation AI and large-scale systems. You will contribute to backend and ML-focused projects, collaborating across teams with a focus on scalable, reliable software.

Applicants should have strong Python or C++ coding skills, ML experience, and a willingness to work on complex problems in a fast-paced environment. In-person interviews are typically required.

Qualifications

• Bachelor's degree or equivalent practical experience required.
• 2 years of experience programming in Python or C++.
• 1 year of experience with Speech/Audio, Reinforcement Learning, ML infrastructure or related ML field.
• 1 year of experience with ML infrastructure (deployment, evaluation, optimization, data processing, debugging).
• Master's degree or PhD preferred.
• 2 years with data structures or algorithms desired.
• Experience developing accessible technologies preferred.

Responsibilities

• Write product or system development code.
• Collaborate with peers and stakeholders through design and code reviews.
• Contribute to documentation and educational content.
• Triage issues and debug across hardware, network, or services.
• Implement solutions in ML areas and contribute to model optimization and data processing.

Skills

Python

C++

Speech/Audio

Reinforcement Learning

ML infrastructure

Other ML field

ML deployment

Data structures

Algorithms

Accessible technologies

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD in CS or related fields

Job description

Google is seeking software engineers in California to work on next-generation AI and large-scale systems. You will contribute to backend and ML-focused projects, collaborating across teams with a focus on scalable, reliable software.

Applicants should have strong Python or C++ coding skills, ML experience, and a willingness to work on complex problems in a fast-paced environment. In-person interviews are typically required.