AI-Driven Full-Stack Engineer — Search Ads & GenAI

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

Job summary

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information. This role focuses on pioneering AI-native ad experiences and advancing the ads product lifecycle with Gemini and LLMs.

As a key team member, you will design, test, deploy, and maintain software solutions, owning features from ground up and tackling 0-to-1 challenges in the Ads business with a strong emphasis on scalable systems.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python or C++.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with one or more of the following: Speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field.

Responsibilities

• Learn more about benefits at Google.
• Work on 0-to-1 problems in Ads business generation space, leveraging AI/ML advancements, including LLMs and Agentic AI.
• Own system design and implementation of new features from ground-up.
• Build agentic systems that automate and significantly scale up iteration velocity.
• Build 10x better AI-first ads experiences on Google Search.
• Design A/B experiment, setup and analysis.

Skills

Python

C++

ML infrastructure

Speech/Audio

Reinforcement learning

GenAI / LLMs

Education

Bachelor's degree or equivalent

Master's degree or PhD in CS

Job description

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information. This role focuses on pioneering AI-native ad experiences and advancing the ads product lifecycle with Gemini and LLMs.

As a key team member, you will design, test, deploy, and maintain software solutions, owning features from ground up and tackling 0-to-1 challenges in the Ads business with a strong emphasis on scalable systems.