Senior Software Engineer, Performance

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 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.
• Experience in C, C++, and Python for high-performance application development, Computer Architecture, Performance Analysis for bottleneck identification, and Simulation for architectural exploration.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 3 years of experience in performance modeling and simulation tools.
• Strong understanding of computer architecture, operating systems, and networking.
  
• Ability to work independently and as part of a team.
• Excellent problem-solving and analytical skills.
  
  

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 Platform Enablement team is responsible for the development, bringup and qualification, deployment, and sustaining quality of our custom silicon. We plan and integrate complex hardware and software stacks and operate them on emulation, simulation and FPGA platforms for pre-Silicon validation. We engage in ASIC Modeling, Prototyping, HW/SW Co-design, Functional bringup and performance benchmarking. We create software-based custom test cases, workloads, test generators, infrastructure, analysis tools, and debugging tools. In later phases, we are responsible for silicon bringup, validation, characterization and qualification, and sustaining programs and their quality. We help ensure our fleet runs at maximum efficiency, and when problems do arise we help debug and root cause those issues.

The ML, Systems, & 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 $166,000-$244,000 + 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

• 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.
  
• Work with the team to develop tracing technology, collect Google workload traces for analysis and drive processor development
  
• Help improve the capability of tracing and expanding the reach of our analysis
  
• Help Google improve our bottomline by improving the fleet efficiency and informing future Google SoC designs
  
• Use an open source JIT instrumentation tool to capture our application behavior on a target platform.