Senior Software Engineer, Cloud GenAI Infrastructure, Vertex AI, Model Efficiency

Socket.dev; Sunnyvale (CA); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Equity

Bonus target

Job summary

Google is hiring software engineers to develop next-generation technologies that power billions of users worldwide. The role focuses on scalable systems across the full stack, with opportunities to switch teams as Google evolves.

The Google Cloud AI Research team tackles AI challenges aligned with Google Cloud’s mission, collaborating with product teams to bring innovations to real-world impact for customers.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 1 year of experience building and developing large-scale infrastructure or distributed systems.
• 1 year of experience with data structures and algorithms.

Responsibilities

• Write product or system development code.
• Review code developed by other developers and provide feedback to ensure best practices.
• Contribute to existing documentation or educational content and adapt content based on product updates.
• Triages product or system issues and debugs/tracks/resolves impact on hardware, network, or service operations.

Skills

Software development

Distributed systems

Data structures & algorithms

Programming languages

Education

Bachelor's degree

Master's degree

Tools

Go

Rust

Java

Job description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 1 year of experience building and developing large-scale infrastructure or distributed systems.
• 1 year of experience with data structures and algorithms.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• Experience developing accessible technologies.
• Experience in backend coding languages such as GOLang, Rust, or Java.
• Experience in ML model coding languages (e.g., Python).

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.The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

• Write product or system development code.
• 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.