Senior Software Engineer, Data and Infrastructure, Professional Intelligence, DeepMind
DeepMind
Mountain View, CA · Posted October 30, 2026
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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.
November 2026
- #1Best cities for AI-skill jobs45% · of 100
- #1Best cities for AI-skill jobs in the West Coast45% · of 71
- #1Best cities for mid-career professionals in the West Coast68% · of 71
- #1Best all-round cities for mid-career professionals in the West Coast85 / 100 · of 39
- #1Best all-round cities for AI careers in the West Coast96 / 100 · of 39
- #2Best cities for finance pay after cost of living$161k · of 35
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
Data & Analytics jobs · Top Data & Analytics employers · All rankings
Pay compared with the market
This listing does not state pay. Across 1,097 open senior software engineer listings that state pay, the middle half runs $170,000 to $222,500 and the median is $200,000.
Listed pay is what employers advertise, not what people are paid.
Senior 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.
Skills this job asks for
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About the job
Minimum qualifications: Bachelor's degree in Computer Science, or equivalent practical experience. Experince in Python with modern toolchains and frameworks (e.g., uv, ruff, FastAPI, Pydantic). Experience building and operating data pipelines (e.g., one or more of Apache Beam, Dataflow, Flink, and Spark), and with trade-offs between batch and streaming designs. Experience with data storage solutions (e.g., SQL/Postgres, NoSQL, blob storage, search indexes, vector databases) and the trade-offs between them. Experience using coding agents to develop code and tests to specification.