← Search all jobs

Software Engineer, AI/ML, ML Infrastructure, Search Ads

Google

Listing collected from Google's career site. NextChapter is independent of Google.

Mountain View, CA · Posted November 12, 2026

Just laid off? Start here: a plan for the first weeks

See every open role at Google

More in California job market · Software Engineer jobs in Mountain View, CA (52) · All Software Engineer jobs (2,097) · Technology & Software · Data & Analytics jobs

Similar jobs

Where Mountain View, CA ranks

Where Mountain View, CA placed in our monthly rankings, month by month. Each month stays online at its own address.

Pay compared with the market

This listing does not state pay. Across 471 open software engineer listings that state pay, the middle half runs $160,000 to $239,500 and the median is $197,500.

Listed pay is what employers advertise, not what people are paid.

Software Engineer salaries by state · Check your own pay

How AI is used in this kind of work

Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Google has filed one layoff notice in the last twelve months, covering 52 workers, most recently August 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

About the job

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages. 1 year of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging). 1 year 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. Experience with Machine Learning systems or Large Language Models (LLMs). Experience designing system architecture for enterprise computing environments supporting AI/ML workloads.