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.
In this role, you will work on bringing AI to Google Cloud customers and developers around the globe. You will build the next generation of AI-powered systems and applications across the full stack of AI from models and APIs, through engineering and agents building blocks, to specialized models and applications.
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.
Responsibilities
- Design and build machine learning (ML) pipelines. Evaluate, integrate, and optimize ML models and agentic workflows.
- Lead the design of generative AI solutions, optimize ML infrastructure, and guide the development of data preparation and model optimization strategies.
- Design, develop, test, deploy, maintain, and enhance large-scale AI-powered platforms and applications.
- Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
- Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in ML engineering including production environments.
- 5 years of experience in software development, including experience in software design, architecture, and shipping production-grade systems.
- 3 years of experience leading technical project strategy and ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience in testing and launching scalable software products.
Preferred qualifications:
- Master's degree in Computer Science or other technical field.
- 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 with genAI techniques (e.g., LLMs, multimodal, large vision models) or with genAI-related concepts (e.g., evaluations, language modeling, computer vision).