Field Solutions Developer III, Generative AI, Google Cloud Full-time

Minimum qualifications:

• Bachelor’s degree in Science, Technology, Engineering, Math, or equivalent practical experience.
• 7 years of experience in AI applications (e.g., deep learning, NLP, computer vision, or pattern recognition).
• Experience in statistical programming language (e.g., Python), applied machine learning techniques, and using OSS frameworks (e.g., TensorFlow, PyTorch).
• 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 with one or more from the following ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.
• Experience training and fine tuning models in large scale environments (e.g., image, language, recommendation) with accelerators.
• Experience with distributed training and optimizing performance versus costs.
• Experience with CI/CD solutions in the context of MLOps and LLMOps including automation with IaC (e.g., using terraform).
• Experience in systems design with the ability to design and explain data pipelines, ML pipelines, and ML training and serving approaches.

About the job

As a Generative AI Field Solutions Developer, you will play a pivotal role in supporting our Google Cloud business organization. Your primary responsibility will be to construct rapid prototype Generative AI applications tailored to Google Cloud customers, catering to a diverse clientele ranging from early stage startups to prominent Fortune 500 companies.

You will leverage the Generative AI technologies to develop innovative solutions and validate their efficacy. You will be tasked with swiftly showcasing the latest Generative AI capabilities through direct collaboration with customers. You will be instrumental in materializing functional solutions on the Google Cloud platform. You will have close collaboration with our product team to eliminate obstacles and shape the future trajectory of our offerings.

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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 $171,000-$257,000 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

• Be a trusted advisor to our customers by understanding the customer’s business process and objectives. Design 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.