15 years of experience in software development, or 10 years with an advanced degree in Computer Science, Mathematics, Statistics, or Engineering. ~ Experience in hardware and software design, data structures and algorithms, debugging, and with customer-facing products. Master's degree in a relevant field. Ability to work cross-functionally, partnering with groups such as Sales, Developing, Product Management, Product Marketing, UX, and UI, brokering trade offs with stakeholders and understanding their needs.

As the Principal Developer, you will be responsible for driving the Google Cloud Machine Learning Compute Services technical strategy, enabling highly scalable ML services powered by both GPUs and TPUs. You'll provide technical leadership in this critical emerging AI/ML cloud use-case. In this role, you will drive, execute, and deliver on the tech strategy for Cloud ML Compute’s overall ML services design for very large scale training and inference on GCP, as well as how these connect nicely to other GCP services such as GKE and Vertex AI.

We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably.



Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

For US Candidates: The US base salary range for this full-time position is $278,000-$399,000 + bonus + equity + advantages. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.

Develop a strategic vision for the Google Cloud Platform organization to constantly innovate and implement novel solutions for next-generation ML and HPC infrastructure services. Design, build, and deploy solutions that leverage GPU, TPU, and highly-scalable hardware and software infrastructure to deliver compelling solutions for GPU, TPU, ML, and HPC workloads. Manage exceptional scheduling and resource management initiatives to optimize GCP service offerings for batch workloads for the key technical computing and machine learning use-cases.

Influence and establish developing best practices through solid design decisions, processes, and tools. #

📌 Principal Developer, Machine Learning Compute Services, Google Cloud (Montreal)
🏢 Google
📍 Montreal