Job description

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. As a Generative Artificial Intelligence (AI) Specialist, you will work with Product Development and Technical Sales teams as an Generative AI subject matter expert to bring Google Cloud AI products to customers and partners. In this role, you will help prospective customers and partners understand the power of Google AI, explaining technical features, helping customers design architectures, build AI powered applications, and problem-solving any potential roadblocks. You will also have the opportunity to help customers leverage Google Cloud’s Generative AI services, including large language models and specialized Machine Learning (ML) hardware developed by Google. The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google . • Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers. • Provide AI expertise to support the technical relationship with Google’s customers, manage product and solution briefings, create demos, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Google Cloud. • Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to implement a complete solution Google Cloud. • Support developers, creators, and enterprises to leverage Google’s Generative Language APIs so they can build their own AI products in the future. • Travel to customer sites, conferences, and other related events as needed. • Bachelor's degree or equivalent practical experience. • 8 years of experience in software development. • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). • 2 years of experience with GenAI techniques (e.g., LLMs, multi-modal, large vision models) or with GenAI-related concepts (e.g., language modeling, computer vision). • 2 years of experience as a Technical Solution Architect in a cloud computing environment, or in a customer-facing role. Minimum qualifications: • Bachelor's degree or equivalent practical experience. • 8 years of experience in software development. • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. • 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). • 2 years of experience with GenAI techniques (e.g., LLMs, multi-modal, large vision models) or with GenAI-related concepts (e.g., language modeling, computer vision). • 2 years of experience as a Technical Solution Architect in a cloud computing environment, or in a customer-facing role. Preferred qualifications: • Master’s degree or PhD in Engineering, Computer Science, or a related technical field. • 8 years of experience with data structures and algorithms. • 3 years of experience in a technical leadership role leading project teams and setting technical direction. • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. • Experience building AI and machine learning solutions, machine learning operation frameworks like Kubeflow, and leveraging specific machine learning architectures (e.g., deep learning, LSTM, etc.). • Understanding of AI models, large language models, and AI specialized infrastructure as it relates to AI trends and issues within businesses.

Requirements

Must-haves

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to implement a complete solution Google Cloud.
Support developers, creators, and enterprises to leverage Google’s Generative Language APIs so they can build their own AI products in the future.
Travel to customer sites, conferences, and other related events as needed.
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
2 years of experience with GenAI techniques (e.g., LLMs, multi-modal, large vision models) or with GenAI-related concepts (e.g., language modeling, computer vision).
2 years of experience as a Technical Solution Architect in a cloud computing environment, or in a customer-facing role.
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
2 years of experience with GenAI techniques (e.g., LLMs, multi-modal, large vision models) or with GenAI-related concepts (e.g., language modeling, computer vision).
2 years of experience as a Technical Solution Architect in a cloud computing environment, or in a customer-facing role.
8 years of experience with data structures and algorithms.

Nice-to-haves

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
Experience building AI and machine learning solutions, machine learning operation frameworks like Kubeflow, and leveraging specific machine learning architectures (e.g., deep learning, LSTM, etc.).
Understanding of AI models, large language models, and AI specialized infrastructure as it relates to AI trends and issues within businesses.

Application prep

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Keywords to mirror

aimachine learningml

Platform: google
Effort: medium

Benefits

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