Staff Software Engineer, AI/ML Data Processing

corporate_fareGoogleplaceSunnyvale, CA, USA

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development.
  
• 8 year of experience with distributed systems and cloud technologies.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years 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.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures and algorithms.
• 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.

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.

In this role, you will be responsible for working with and evolving the team’s core data processing libraries. You will be working with the team’s top first-party (1P) customers in enabling their JAX-based trainers and modernizing their Artificial Intelligence/Machine Learning (AI/ML) data processing infrastructure. You will also be responsible for working with executive engineers in the team to lead the development of the next generation of online data processing infrastructure.

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 $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

• Drive the development of high-performance data processing of features and Application Programming Interfaces (APIs) to enable new use cases.
• Collaborate across Google's ML ecosystem on integrations with other components of ML infrastructure such as training, checkpointing, and inferencing.
• Optimize performance and efficiency of the implementation.
• Find creative ways to make online data processing effective and easy to use, enabling training jobs that use hundreds or thousands of accelerators.
• Work directly with top first-party (1P) users (e.g., Gemini, YouTube, Search, Ads, and others) on redefining the data pipelines for the future in conjunction with JAX and ML Pathways.