Software Engineer III, ML Performance at Google

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

202000.0

Posted On

11 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Development, Computer Architecture, Performance Analysis, Performance Modeling, ML Infrastructure, Data Processing, Debugging, Data Analysis, Visualization Tools, GPU, TPU, Algorithms, Machine Learning, Compiler Optimization, Code Generation, Runtime Systems

Industry

Software Development

Description

MINIMUM QUALIFICATIONS: * Bachelor’s degree or equivalent practical experience. * 2 years of experience with software development in one or more programming languages. * 2 years of experience with computer architecture, performance analysis, and performance modeling. * 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). * 2 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging. * Experience working with Graphics Processing Unit (GPU) or Tensor Processing Unit (TPU). PREFERRED QUALIFICATIONS: * Master's degree or PhD in Computer Science or related technical fields. * 2 years of experience with data structures or algorithms. * Experience developing accessible technologies. * Experience in tailoring algorithms and Machine Learning (ML) models to exploit ML accelerator architecture strengths and minimize weaknesses. * Experience with machine learning, compiler optimization, code generation, and runtime systems for GPU architectures. * Understanding of modern GPU architectures (e.g., NVIDIA, AMD), memory hierarchies, and performance bottlenecks. 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 ML, Systems, and Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers. 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 [https://careers.google.com/benefits/]. RESPONSIBILITIES: * Write 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). * 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.

Responsibilities

Write product or system development code and participate in design reviews with peers and stakeholders. Triage product or system issues and debug by analyzing the sources of issues and their impact on operations and quality.