- Experience with coding in standard programming frameworks (e.g., Python or R) and machine learning frameworks (e.g., Tensorflow, Pytorch, Keras, etc.).
- Experience with Cloud Computing as a technical sales engineer or in a customer-facing role, within a startup ecosystem.
- Experience with AI cloud infrastructure (e.g., hardware shapes, sizes, auto-scaling, auto-provisioning, etc.).
- Experience with designing, building, and operating machine learning solutions leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolution networks, etc.).
- Experience training and fine tuning large models (i.e., image, language, segmentation, recommendation, genomics) with AI accelerators.
- Experience leveraging Cloud-based machine learning solutions.
- Experience with containerization and Kubernetes within the cloud.
- Ability to engage with C-level or executive business leaders and influence decisions.
- Passion for machine learning operations approaches, conceptual related frameworks, and technical implementation based on CI/CD.
About the job
As a Customer Engineer, you will work closely with business development and Sales teams as AI/ML subject matter experts to position the value of Google Cloud to our strategic Startup customers. 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 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 help several AI Startups to understand the power of Google Cloud, explaining technical features, helping customers design architectures, and problem-solving any potential roadblocks. 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. You will also have the opportunity to help customers to leverage specialized machine learning (ML) hardware developed by Google (e.g., Tensor Processing Unit). You will work closely with customers and product development to shape the TPU platform.
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.
- Work with the AI incubation team to identify and qualify business opportunities, understand key customer technical requirements or objections, and develop the strategy to resolve technical blockers.
- Be a trusted advisor to our strategic AI startup customers, to ensure overall cloud strategy, recommending migration approaches, integration strategies, and architecture that leverage Google Cloud AI components and optimized infrastructure.
- Help to understand and incorporate AI accelerators (e.g., GPUs or TPUs) into overall machine learning systems.
- Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on demonstrating features, optimizing model performance, profiling, and benchmarking.
- Influence Google Cloud strategy at the intersection of AI/ML expertise and infrastructure by regular interaction with Product groups.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy
and EEO is the Law.
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