Senior Software Engineer, Generative AI Evaluation Platform - Google
Sunnyvale, CA
About the Job
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with developing infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- Experience in Machine Learning/AI Infrastructure.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 2 years of experience with performance, systems data analysis, visualization tools, or debugging.
- Experience architecting and developing software or infrastructure for scalable, distributed systems and with machine learning technologies.
- Experience developing accessible technologies.
- Experience in code and system health, diagnosis and resolution, and software test engineering.
About the job
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.
Core Machine Learning (ML) is the central machine learning platform team that provides ML software tools, services, solutions, and infrastructure to all the Google product areas, including Search, Ads, YouTube, Cloud, and Maps. The teams goal is to make it easier to perform ML experimentation, development, and productionization, and work with Google Research and DeepMind to bring new ML models and innovation across the stack to market. The Evaluation Platforms team is a sub team of the Core ML Infrastructure team with the mission to accelerate and scale AI through unified evaluation platforms. The team builds Generative AI evaluation platforms across workflows including authoring, execution, and analysis.
The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Write Generative AI evaluation platform and tooling code, and triage product or system issues.
- Participate in, or lead design reviews with peers and stakeholders to decide on available technologies.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- 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.