Research Software Engineer, ML Network Optimization, Google Beam

Research Software Engineer, ML Network Optimization, Google Beam

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Corporate fare Google place Mountain View, CA, USA ;
Seattle, WA, USA ; +2 more ; +1 more

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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Inform Outline X Applicants in San Francisco:
Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Note:

By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA;
Seattle, WA, USA;
San Francisco, CA, USA
.

• 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 人気に with maintaining or launching software products, and 1 year with software design manuscripts.
• 3 years with one or more of:
  Machine Learning Optimization (e.g., quantization, distillation), GPU/TPU hardware architecture, Kernel programming, or specialization in another ML field.
• 3 years with ML infrastructure (e.g., 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 (e.g., CUDA, OpenCL, Vulkan, Triton), compiler technologies (e.g., XLA), and optimizing real-time media pipelines.

Google's software engineers develop the next-generation technologies that transform how billions of users connect, explore, and interact with information and each other. Our products must handle massive scale, going far beyond web search. We welcome engineers from all disciplines—information retrieval, distributed computing, large-scale system design, networking and data storage, security, AI, NLP, UI, mobile, etc.

Google Beam builds advanced software and hardware to enable real‑time conversations for people who are geographically separated, making them feel as though they are in the same room.

As a Research Software Engineer, you join a fast‑moving team at the intersection of computer vision, machine learning, and graphics. Your focus is on turning research into production‑ready systems, bridging high‑level algorithms with low‑level hardware performance. You will help architect transitions to next‑generation GPU platforms and collaborate with researchers and engineers to shape the future of communication.

Labs is dedicated to incubating early‑stage initiatives that support Google’s mission to organize the world’s information. We explore new technologies and build solutions that could transform user experiences and drive long‑term impact.

The US base salary range for this full‑time position is $166,000–$244,000 + bonus + equity + benefits. Pay is determined by role, level, location, and relevant skills, experience, or education. Your recruiter can share more specific guidance for your chosen location during hiring.

Compensation details listed in US postings reflect base salary and exclude bonus, equity, or benefits. Learn more about benefits at Google.

• Research and implement emerging best practices in network design (e.g., quantization, distillation) to accelerate performance without quality loss.
• Lead low‑level performance optimization and develop fast custom kernels to reduce GPU resource usage 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 achieve long‑term gains in the performance of our ML software and hardware stack.

Google is proud to be an equal‑opportunity employer, including affirmative action. We are committed to building a workforce that reflects the users we serve and fostering a culture of belonging, meeting legal requirements for equal employment opportunity across all protected categories. See Google’s EEO policy, Belonging at Google, and How we hire for more details.

English proficiency is required for all roles unless otherwise specified.

To recruitment agencies:
Google does not accept agency resumes. Do not forward resumes to our jobs alias, Google employees, or any other organization. Google is not responsible for fees related to unsolicited resumes.