Software Engineer, AI/ML, Full Stack, Search Ads
Role details
Job location
Tech stack
Job description
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a key member of a small and versatile team, you design, test, deploy and maintain software solutions., * 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.
Requirements
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * 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 (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., * Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience developing accessible technologies.