Field Solution Architect, AI Infrastructure, Google Cloud
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- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
- 7 years of experience with cloud infrastructure (e.g., hardware shapes, sizes, auto-scaling, auto-provisioning), and experience with infrastructure as a service, platform as a service, and software as a service.
- Experience coding in Python, bash scripting, and using OSS frameworks (e.g., TensorFlow, PyTorch, Jax).
- Experience with distributed training and optimizing performance versus costs (e.g., PyTorch FSDP/DeepSpeed, JAX/pjit, bfloat16 mixed-precision, or MLPerf benchmarking).
- Experience with orchestrators (e.g., Slurm, 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 in designing and architecting large-scale AI compute clusters.
- Ability to debug distributed training/inferencing code running.
About the job
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As a Field Solution Architect, your experience and thought leadership 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 solutions using Google Cloud’s flexible and open infrastructure.
In this role, you will identify and assess 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
Responsibilities
- Serve as a trusted advisor to top customers, helping them incorporate artificial intelligence (AI) accelerators into cloud strategies by designing training and inferencing platforms.
- Demonstrate Google Cloud differentiation through Proofs of Concept, feature demonstrations, model performance optimization, profiling, and benchmarking.
- Collaborate seamlessly with the Google Compute Engine AI Infrastructure Dedicated Engineering Team to co-develop code artifacts, best practice documentation, and scalable machine learning (ML) solutions.
- Influence Google Cloud infrastructure strategy by advocating for enterprise requirements and building repeatable assets to enable internal teams and customers.
- Travel to customer sites and industry events as needed to provide direct support and represent Google Cloud AI solutions.
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