Google's Ads Safety team is looking to re-imagine the analyst ecosystem with groundbreaking AI, LLMs, and Agent-powered innovations to safeguard billions of users and ensure Google Ads safety. The goal is to transform existing tools into a self-service tooling platform, improving efficiency and effectiveness in handling complex policy reviews and enforcement at scale.
Requirements
- 2 years of experience in programming in Python or C++.
- 2 years of experience in web technologies, back-end, full-stack development, system design, query optimization, database optimization, problem-solving, front-end development.
- 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.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 3 years of experience with full stack development, across back-end such as Java, Python, GO, or C++ codebases, and front-end including JavaScript or TypeScript, HTML, CSS equivalent.
- 3 years of experience with big data systems and database query optimizations.
- 2 years of experience in applying AI/ML/LLMs to solve real-world problems, particularly in the software development domain.
Responsibilities
- Write product or system development code.
- Design and develop to transform our tools into a self-service tooling platform, from the user interface to integrations to reliable backend services, ensuring exceptional performance and usability.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
- Implement solutions in one or more specialized machine learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing.
- Apply software engineering best practices across the entire development lifecycle, from scalable design and testing to release and production monitoring.
Other
- Equivalent practical experience.
- Versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack.
- Experience developing accessible technologies and user-facing products.
- Familiarity with Google's development, build, test, and production infrastructure.
- US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits.
