Field Solutions Architect, Generative AI, Google Cloud - Warsaw
Since our founding in 1998, Google has grown by leaps and bounds. Starting from two computer science students in a university dorm room, we now have thousands of employees and offices around the world. These Googlers build products that help create opportunities for everyone, whether down the street or across the globe.It starts with how we work together. We’re building a company where people of different views, backgrounds and experiences can do their best work and show up for one another.
Tech stack
AI applications
PyTorch
TensorFlow
OSS
Python
Job description
About the job
As a Generative AI Field Solutions Architect, you will support Google Cloud Sales and Engineering teams to incubate, pilot, and deploy Google Cloud’s industry leading AI/ML and Generative AI technology with AI natives, large enterprises, and early-stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators (TPU/GPU).
In this role, you will identify, assess, and develop Generative AI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. 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. You will work closely with internal Cloud AI teams to remove roadblocks and shape the future of our offerings. You will navigate ambiguity, troubleshoot and find solutions, and learn quickly in a rapidly changing technology space.
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.
Responsibilities:
- Be a trusted advisor to our customers by understanding the customer’s business process and objectives. Architect AI-drive, spanning Data, AI, and Infrastructure, and work with peers to include the full cloud stack into overall architecture.
- Demonstrate how Google Cloud is differentiated by working with customers on PoCs, demonstrating features, tuning models, optimizing model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues training/serving models in a large-scale environment.
- Build repeatable technical assets such as scripts, templates, reference architectures, etc. to enable other customers and internal teams. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.
- Coordinate regional field enablement with leadership and work closely with product and partner organizations on external enablement activities. Travel as needed.
Minimum qualifications:
- Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using Operational Support Systems (OSS) frameworks (e.g., TensorFlow, PyTorch).
- Experience in AI applications (e.g., deep learning, NLP, computer vision, or pattern recognition).
- Experience delivering technical presentations and leading business value sessions.
Preferred qualifications:
- Master's degree in Computer Science, Engineering, or a related technical field.
- Experience designing and deploying one or more from the following Machine Learning frameworks: TensorFlow, PyTorch, JAX, Spark Machine Learning, etc.
- Experience training and fine tuning models in large-scale environments (e.g., image, language, recommendation) with accelerators.
- Experience with CI/CD solutions in the context of Machine Learning Operations and Large Language Model Operations including automation with IaC.
- Experience with distributed training and optimizing performance versus costs.
- Experience in systems design with the ability to architect and explain data pipelines, Machine Learning pipelines, Machine Learning training and serving approaches.
- Health and Wellbeing (Medical, dental, and vision insurance for employees and dependents)
- Financial wellbeing (Competitive compensation, regular bonus and equity refresh opportunities)
- Flexibility and time off (Paid time off, including vacation, bereavement, jury duty, sick leave, parental leave, disability, and holidays)
- Family support and care (Fertility and growing family support, parental leave and baby bonding leave)
- Community and personal development (Educational reimbursement)
- Googley extras (Inspiring spaces to work, recharge, and collaborate with fellow Googlers)