Software Engineer, Search AI Infra Performance

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with machine learning (ML) infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 3 years of experience debugging and optimizing distributed systems.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• Experience developing accessible technologies.
  
• Experience in working with large language models (LLM).
  
• Experience with Search products or infrastructure that uses or is used by generative AI (GenAI) APIs.
• Experience with LLM tuning, reinforcement learning, supervised fine-tuning, prompt optimization, or other ML techniques.

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.

Search artificial intelligence (AI) infrastructure enables the deployment of AI models at Search's scale. We partner with Search AI developers, Google DeepMind, and Core machine learning (ML) to tailor solutions across the ML infrastructure ecosystem.

Our mission is to empower developers with access to Gemini models by optimizing the stack—from orchestration down to the models themselves. We provide the services, tools, and expertise needed for lifecycle management and resource optimization, accelerating AI innovation while eliminating infrastructure overhead for generative AI products.

Responsibilities:

• Design tools and processes to streamline developer experience with large language models (LLMs).
• Ensure models and AI experiences can launch given latency, capacity, and reliability constraints.
• Ensure use of TPU and other machine learning (ML) accelerators.
• Drive optimizations across teams and systems for LLMs for latency and throughput across the Search stack.
• Collaborate with Search ATLs, GDM, CoreML, and Search software engineers (SWEs) and site reliability engineers (SREs).