Software Engineer AI/ML Networking
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in C++, or 1 year of experience with an advanced degree.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- 1 year of experience working with embedded operating systems.
- Experience with network protocol implementation and optimization for high-bandwidth, low-latency environments such as AI/ML clusters.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience with data structures and algorithms.
- Experience developing accessible technologies.
- Experience with Machine Learning 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.
Come join Google's Network Infrastructure Team (within Systems Infrastructure) in the Cloud site in Durham, NC!
US: $147000 - $211000 (USD) + 15% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Write product or system development code.
- Contribute to existing documentation or educational content and adapt content based on product or program updates and user feedback.
- Implement solutions in one or more specialized Machine Learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing.
- Build and test software in C++ for use on Google's ML library solutions, smart NICs and develop next generation AI/ML networking solutions as well as smart NICs at Google, while taking the projects through development into production.

