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.
  

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 1 year of experience in a technical leadership role.
  
• Experience developing accessible technologies.
• Experience in machine learning.

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.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

The Machine Learning Benchmarking team provides self-service, automated performance monitoring and diagnostic systems for ML projects at Google. We provide product area leads and executives with visibility into benchmark efficiency gains across the fleet, spanning training and serving. We help product areas track business critical models for quality and performance, with automatic detection, culprit finding, enable visibility into industry popular model performance on Google Infrastructure, and drive improvements.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

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 and test product or system development code.
  
• Participate in, or lead design reviews with peers and stakeholders to decide amongst 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).
  
• Develop key benchmarking tools, visualization methodologies, and innovative analysis pipelines to standardize ML Performance management at Alphabet scale.
• Work with large ML deployment infrastructure to integrate benchmarking, propose new benchmarking paradigms (such as LLM Performance parameters), and innovate on insightful benchmark analysis dashboards to drive performance improvements across major stakeholders.