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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Software Engineer, ML Network Optimization, Google Beam - **Company:** Google LLC - **Location:** San Francisco, CA, United States - **Salary:** $166,000.0 - $244,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Nvidia CUDA, Computer Engineering, Data Structures, Software Debugging, Distributed Systems, Google Tools, Design of User Interfaces, Push Technology, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Network Planning and Design, OpenCL, Performance Tuning, Software Architecture, Software Engineering, Systems Architecture, Data Processing, Data Storage Technologies, Model Validation, Information Technology, Search Engines, Machine Learning Operations, Hardware Infrastructure, Vulkan Graphics API, Network Optimization, Programming Languages - **Published:** August 31, 2026 - **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-B2EAE62A1ECE335883/ ## About the Role * Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. * 5 years of experience with software development in one or more programming languages, including C+ and Python. * 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 one or more of the following: Machine Learning Optimization (eg, quantization, distillation), GPU/TPU hardware architecture, Kernel programming, or specialization in another ML field. * 3 years of experience with ML infrastructure (eg, model deployment, model evaluation, optimization, data processing, debugging)., * Master's degree or PhD in Computer Science, Computer Engineering, or a related technical field. * 5 years of experience with data structures and algorithms, and hardware-software co-design. * 1 year of experience in a technical leadership role or driving architectural transitions. * Experience with Kernel programming (eg, CUDA, OpenCL, Vulkan, Triton), compiler technologies (eg, XLA), and optimizing Real Time media pipelines. * Experience developing accessible technologies. ## Description 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. Google researchers and engineers are turning science fiction into reality. Google Beam is developing advanced software and hardware technology to enable people who are separated by distance to experience a conversation as if they were together in the same room. As a Research Software Engineer, you will join a creative, fast-moving team at the intersection of computer vision, machine learning, and graphics. While we push the boundaries of what is possible with novel research, your focus will be on making that research viable for production. You will bridge the gap between high-level algorithms and low-level hardware performance, architecting the transition to next-generation GPU platforms. You will work alongside researchers and engineers to invent the future of communication. Labs is a group focused on incubating early-stage efforts in support of Google's mission to organize the world's information and make it universally accessible and useful. Our team exists to help discover and create new ways to advance our core products through exploration and the application of new technologies. We work to build new solutions that have the potential to transform how users interact with Google. Our goal is to drive innovation by developing new Google products and capabilities that deliver significant impact over longer time frames. 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 * Research and implement emerging best practices in network design (eg, quantization, distillation) to accelerate network performance without loss of quality. * Lead low-level performance optimization efforts and write fast custom kernels to reduce per-call GPU resource requirements and latency. * Analyze and profile complex ML models and graphics pipelines to identify and resolve performance bottlenecks. * Collaborate with hardware and compiler teams to influence next-generation architecture and software stack requirements. * Navigate hardware-software co-design to facilitate long-term gains in the performance of our ML software and hardware stack. ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [30 Golden Rules of Deep Learning Performance](https://www.wearedevelopers.com/videos/11-30-golden-rules-of-deep-learning-performance) - [Humanoid Runs Wild, Google Rewrites Headlines and Slow AI - Justin Halsall and Schepp](https://www.wearedevelopers.com/videos/1843-humanoid-runs-wild-google-rewrites-headlines-and-slow-ai-justin-halsall-and-schepp) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) - [Ask Your Code](https://www.wearedevelopers.com/videos/603-ask-your-code) - [The weekly developer show: Boosting Python with CUDA, CSS Updates & Navigating New Tech Stacks](https://www.wearedevelopers.com/videos/1293-the-weekly-developer-show-boosting-python-with-cuda-css-updates-navigating-new-tech-stacks) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)