AI/ML Software Engineer – Keywordless Ads Platform

Socket.dev; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Benefits offered by this job

Bonus target 15%

Equity

Benefits

Job summary

Google is seeking software engineers in Mountain View, CA to advance AI-powered ad automation and related ML infrastructure. You will contribute to end-to-end ML workflows, model deployment, and performance optimization for high-traffic ad services.

Ideal candidates have strong coding skills in Python or C++, hands-on ML experience, and a passion for scalable systems and data-driven decision making.

Qualifications

• Bachelor’s degree or equivalent practical experience required.
• 2 years of experience programming in Python or C++.
• 1 year of experience with generative AI, reinforcement learning, large language modeling, model processing, or related ML field.
• 1 year of experience with end-to-end machine learning (model deployment, evaluation, data processing, debugging).

Responsibilities

• Write product or system development code.
• Develop and deploy new ML/LLM models to impact Google, advertisers and users.
• Manage complex, open-ended engineering problems related to ad relevance, query understanding, and large-scale system optimization.
• Triage product or system issues and debug/track/resolve by analyzing sources of issues and impact on hardware, network, or service operations.
• Implement solutions in specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing.

Skills

Python

C++

Generative AI

End-to-End ML

Education

Bachelor’s degree or equivalent practical experience

Job description

Google is seeking software engineers in Mountain View, CA to advance AI-powered ad automation and related ML infrastructure. You will contribute to end-to-end ML workflows, model deployment, and performance optimization for high-traffic ad services.

Ideal candidates have strong coding skills in Python or C++, hands-on ML experience, and a passion for scalable systems and data-driven decision making.