Software Engineer, XLA-TPU Debugging Tools
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in the C++ programming language.
- 2 years of experience building developer tools (e.g., compilers, automated releases, code design and testing, test automation frameworks).
- 2 years of experience with developing large-scale machine learning infrastructure, distributed systems or networks.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience developing ML compilers or low-level debugging tools.
- Experience with machine learning frameworks such as JAX.
- Experience with numerical issues such as floating point, numerical stability, error analysis, etc.
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 is part of the ML Compilers organization, which is responsible for developing the compilers to accelerate ML models (training & inference) on TPU and GPU. Our users include numerous Google’s Product Areas (Ads, Search, Research, etc.), Deepmind, Waymo, as well as external Cloud customers.
Our team works across the stack of ML compilers and ensures they scale to larger models and connect to the major ML frameworks.
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 $141,000-$202,000 + 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
- Design and build tooling that enables distributed debugging of numerical issues in large-scale production ML workloads.
- Identify sources of numerical instability in production ML workloads, and design and implement software changes that eliminate or mitigate the instability.
- Work with modeling teams to root-cause and fix numerical problems in their ML models.
- Improve understanding of numerics in ML models by analyzing and documenting compiler and hardware internals that affect numerics.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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