Machine Learning Engineer, AI/ML Expert for Agents and TrustGraph, Google Ads
ML engineer on Google's Agents and TrustGraph team (Google Ads) building GenAI/LLM agent systems, adversarial red-teaming frameworks, and high-throughput graph pipelines that detect abuse and fraud across Google's ad ecosystem. Core stack: Python, distributed systems, and large-scale ML infrastructure.
- Compensation
- $147K–$210K / yr
- Location
- Mountain View, CA, USA
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 1+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- Bachelor's degree or equivalent practical experience
- 2 years of software development experience in Python or more programming languages, or 1 year with an advanced degree
- 2 years of experience with distributed systems
- 1 year of experience with end-to-end machine learning (model deployment, evaluation, data processing, debugging)
- Experience with GenAI techniques (LLMs, Multi-Modal, Large Vision Models) or GenAI-related concepts (language modeling, computer vision)
Nice to have
- Master's degree or PhD in Computer Science or related technical field
- 2 years of experience with data structures and algorithms
- Experience developing accessible technologies
- Experience with large-scale datasets, graph systems, web/app infrastructure, or GenAI/LLM-based systems
- Experience building LLM agents, multi-agent orchestration frameworks, automated red-teaming/adversarial simulation, or evaluation pipelines
- Experience with large-scale graph databases/algorithms (e.g., Spanner, entity resolution, clustering, graph mining) or web/app crawling and anti-cloaking technologies
Full 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.
The Agents and TrustGraph (ATG) team is a broad, cross-cutting horizontal organization spanning Ads Privacy and Safety, Consumer Trust and Safety, and partner Product Areas across Google. We build the foundational AI platforms, relational intelligence infrastructure, and adversarial crawling systems that protect Google’s users, advertisers, and publishers from bad actors.
As online abuse and fraud grow in volume and sophistication—increasingly powered by generative AI—static rules and reactive manual workflows are no longer enough. Because ATG operates as a horizontal pillar with Google-wide fan-out, engineers on our team are not siloed into a single narrow product. Instead, you will have the flexibility to work across projects and pivot to where the highest leverage lies.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex issues. Join us to work on AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
- Contribute to existing documentation or educational content, adapt content based on product/program updates and user feedback.
- Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, performance enhancements.