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Field Solution Architect, Search AI, Google Cloud

Taipei City, Taiwan (On-site)

Field Solution Architect, Search AI, Google Cloud

4 Days ago • 6 Years + • Artificial Intelligence

About the job

Summary_{By Outscal}

5 skills required for this role

Boost these skills to join the top 1% applicants for this job

Must have:

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.

Good to have:

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 semantic search frameworks and tools/databases such as LangChain, Faiss, and Pinecone.
Experience with implementing search concepts, such as indexing, scoring, relevancy, faceting, and query rewriting and expansion.
Understanding of nearest neighbor search concepts.

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Minimum 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.

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 semantic search frameworks and tools/databases such as LangChain, Faiss, and Pinecone.
Experience with implementing search concepts, such as indexing, scoring, relevancy, faceting, and query rewriting and expansion.
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.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.