Sr. Kubernetes Admin/Engineer – HYBRID

Job Overview

logoMinimum qualifications:

Bachelor’s degree in Computer Science, Data Science, or equivalent practical experience.6 years of experience working in AI/ML as a technical sales engineer or
in software engineering.Experience in Python and Machine learning frameworks (e.g., TensorFlow, PyTorch).Experience in Generative AI as a user or a developer.Experience delivering technical presentations and leading business
value sessions in English to support client relationship management in this region.

Preferred qualifications:

Experience in systems design, with the ability to architect and explain data pipelines, Machine Learning (ML) pipelines, and ML training and serving approaches.Experience with full-stack ML engineering to seamlessly
combine retrieval-based knowledge and generative text generation to implement and optimize RAG models using first-party and OSS models.Experience with implementing search concepts, such as indexing, scoring, relevancy, faceting,
and query rewriting and expansion.Experience with semantic search frameworks and tools/databases such as LangChain, Faiss, and Pinecone.Understanding of nearest neighbor search concepts.

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 AI/ML and Generative AI technology with AI
native customers, 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 GenAI 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
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.

Responsibilities

Advise 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.Work with customers, demonstrate features, tune models, optimize model performance, profiling, and bench marking. Troubleshoot and find solutions
to issues training/serving models in a large scale environment.Build repeatable technical assets such as scripts, templates, reference architectures 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 with
product and partner organizations on external enablement activities.Travel as needed.

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. If you have a disability or special need that requires accommodation, please let us know by completing
our Accommodations for Applicants form .

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