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 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.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- Experience with AI and agentic tooling for development and research.
Preferred qualifications:
- Master's degree or PhD.
- 5 years of experience with data structures/algorithms in C++ and Python.
- Experience with an emphasis on algorithms, systems and tools for ML performance projections and evaluation.
- Experience designing or implementing components of a Deep Learning Compiler Stack (e.g., XLA, MLIR, TVM, ONNX Runtime).
- Experience in low-latency systems programming (e.g., C/C++) and optimizing data movement across the memory hierarchy (e.g., caches, HBM, I/O).
- Experience in performance engineering for ML/AI, including the design and optimization of GPU/TPU kernels, deep learning compilers, or low-latency systems infrastructure.
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 role of Performance Engineer is to improve and validate overall ML performance projections and validations across key workloads, software stack and hardware (GPU, TPU, system). You interact with product groups, software and hardware teams, and research. You develop custom software tools for performance projections, validations, cost metrics, benchmarking, profiling, analysis and reporting. You will contribute to innovations and contributions to advanced Artificial Intelligence (AI) and agentic approaches to Hardware/Software (HW/SW) co-design.
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.
Responsibilities
- Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
- Build, maintain and validate HW/SW tooling to enable reliable and fast evaluation of options and solutions for ML/AI infrastructure (C++, Python).
- Build and maintain tools and methods to measure, visualize and analyse ML HW/SW performance.
- Define, implement and validate performance and cost metrics relevant for existing and future workloads and systems.
- Collaborate with other teams (hardware, compiler, ML research) to improve the end to end flow and results.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also
Google's EEO Policy and
EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our
Accommodations for Applicants form.
