Field Solution Architect II, AI Infrastructure, West, Google Cloud

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 5 years of experience with cloud infrastructure (hardware shapes, sizes, auto-scaling, auto-provisioning, etc.), working with infrastructure as a service, platform as a service, or software as a service.
• Experience with distributed training and optimizing performance versus costs.
• Experience coding in Python, bash scripting, and using OSS frameworks such as TensorFlow, PyTorch, Jax, etc.
• Experience with orchestrators such as Slurm or Kubernetes.
• Experience building and operationalizing machine learning models.

Preferred qualifications:

• Experience training and fine tuning large models (i.e., image, language, segmentation, recommendation, genomics) with accelerators.
• Experience with containerization, K8s, Kubernetes on cloud.
• Experience with running MLPerf benchmarks.
• Experience with performance profiling tools (i.e., Tensorflow profiler, PyTorch profiler, Tensorboard).
• Experience designing/architecting large-scale AI compute clusters.
• Ability to debug distributed training/inferencing code running.

About the job

As an Enterprise AI Infrastructure Field Solution Architect, you will support Google Cloud sales teams to incubate, pilot, and deploy Google Cloud's industry leading AI/ML accelerators (TPU/GPU) at AI innovators, large enterprises, and early stage AI startups. You will help customers innovate faster with state of the art solutions using Google Cloud's flexible and open infrastructure.

In this role, you will identify and assess large-scale AI opportunities that would benefit from AI optimized infrastructure. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance. Along the way, you would work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings.

Google Cloud accelerates every organization's ability to digitally transform its business and industry. 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.

The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

• Become trusted advisors to our customers, helping them understand and incorporate AI accelerators into their overall cloud strategy by designing large-scale training and inferencing platforms, using the latest and greatest accelerators Google Cloud has to offer.
• Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and benchmarking.
• Build repeatable assets to enable other customers and internal teams.
• Influence Google Cloud strategy at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.
• Travel to customer sites and events as needed.