ML Compiler Software Engineer, XLA TPU Horizontal Scaling

Key Skills

Algorithms, C++, Cloud computing, Data Analysis, Data structuring, Data Visualization, Debugging, Design, GPUs, High performance computing- HPC, Machine learning techniques, Optimization, Software Development

Job Description

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages, and 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 performance, systems data analysis, visualization tools, or debugging.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• Experience in C++.
• Experience in compilers.
• Experience in Machine Learning and High Performance Computing (HPC).
• Experience optimizing programs at distributed scale.
• Comfortable debugging and programming concurrent/parallel computations.

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.

Our team develops the XLA TPU/GPU parallelizing compiler used to partition, optimize, and run large-scale machine learning models across multiple TPU/GPU accelerators for internal and external customers. The XLA Horizontal Scaling Team’s software stack includes the XLA SPMD partitioner, collective and scheduling optimizations, and code generation.

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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 $157,000-$235,000 + 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 for new hire 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 product or system development code.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Contribute to a compiler which scales-out machine learning models across accelerators like TPU/GPU at Google and Cloud. 
• Conduct static and runtime performance analysis of important large-scale production models.
• Design and implement performance optimizations and critical features, which increase the velocity of important production teams.