Software Engineer

About The Job

Google's engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information. You'll be at the forefront of innovation, developing systems and AI and Machine Learning solutions. As a PhD graduate, your research expertise is invaluable. Explore a variety of projects, collaborate with various teams, and contribute to products that are changing the world, across many product areas, including AI & Infrastructure, Cloud, YouTube, Search, Ads, and more. Google offers exciting opportunities as it is a leading producer and consumer of ML and AI technology, with decades of experience in designing, deploying, and using ML software and custom ML hardware infrastructure at massive scale.

Key Responsibilities

• Collaborate or lead on team projects to carry out design, analysis, and development of advanced ML systems across the stack using your research expertise.
• Support building end-to-end ML Systems that involves working across the full stack, from low-level hardware acceleration and compiler optimizations to high-level model architecture and production APIs, transforming your research expertise into robust, scalable products.
• Optimize complex system performance by analyzing and fixing performance bottlenecks, memory inefficiencies, and errors in production systems to meet stringent customer goals.
• Elevate engineering excellence by writing well-tested code, conducting code reviews, and fostering a culture of quality by advocating best engineering practices.

Requirements & Tech Stack

• PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field, or equivalent practical experience.
• Experience coding in one of the following programming languages: Python, C, C++, Java, JavaScript, or Golang.
• Experience in Machine Learning or Artificial Intelligence.
• Familiarity with model architectures (e.g., CNNs, NLP Transformers, Diffusion/Vision Transformers).
• Experience developing with Rust and modern deep learning frameworks such as PyTorch, JAX, or TensorFlow.
• Availability to start in a full-time role in 2027.

Qualifications

• Research experience in designing, developing, or applying ML/AI systems or applications in a large-scale distributed environment.
• Experience in designing, training, or refining complex ML/AI models.
• Experience in building a stack for an AI-powered application, including data ingestion and processing pipelines, building APIs, and connecting the model to a user-facing interface.

This position may require in-person interviews.

Preferred working locations: Sunnyvale, CA, USA; Atlanta, GA, USA; Kirkland, WA, USA; Madison, WI, USA; Mountain View, CA, USA; New York, NY, USA; Raleigh, NC, USA; Durham, NC, USA; San Bruno, CA, USA; Seattle, WA, USA.