Google Inc.
Staff Software Engineer, AI/ML Agentic Migrations
Google Inc., Mountain View, California, us, 94039
Staff Software Engineer, AI/ML Agentic Migrations
corporate_fare Google place Mountain View, CA, USA
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Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience in testing and launching software products, and 3 years of experience with software design and architecture.
5 years of experience in leading Machine Learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
2 years of experience with Generative AI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with Generative AI-related concepts (e.g., language modeling, computer vision).
Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
Experience with coding in Python.
Experience with ML model training and evaluation.
Experience with ML Frameworks (e.g., Jax, Keras, TensorFlow, PyTorch), or machine learning production infrastructure.
Experience with Agentic tools, prompt engineering, context management.
Excellent system designing skills to understand the Machine Learning (ML) pipelines and take technical decisions in the greenfield project.
About the job 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.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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
Design and development of related Machine Learning (ML) Frameworks Agentic solutions.
Help to build a multi-agent system to deliver significant and measurable time savings on real-world migrations of ML models and their training pipelines.
Work in collaboration with ML Infrastructure teams and Product Areas of ML Infrastructure (e.g., YouTube, Search).
Give contributions to the Artificial Intelligence (AI) for AI roadmap.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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Apply
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience in testing and launching software products, and 3 years of experience with software design and architecture.
5 years of experience in leading Machine Learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
2 years of experience with Generative AI techniques (e.g., Large Language Models (LLMs), Multi-Modal, Large Vision Models) or with Generative AI-related concepts (e.g., language modeling, computer vision).
Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
Experience with coding in Python.
Experience with ML model training and evaluation.
Experience with ML Frameworks (e.g., Jax, Keras, TensorFlow, PyTorch), or machine learning production infrastructure.
Experience with Agentic tools, prompt engineering, context management.
Excellent system designing skills to understand the Machine Learning (ML) pipelines and take technical decisions in the greenfield project.
About the job 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.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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
Design and development of related Machine Learning (ML) Frameworks Agentic solutions.
Help to build a multi-agent system to deliver significant and measurable time savings on real-world migrations of ML models and their training pipelines.
Work in collaboration with ML Infrastructure teams and Product Areas of ML Infrastructure (e.g., YouTube, Search).
Give contributions to the Artificial Intelligence (AI) for AI roadmap.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
#J-18808-Ljbffr