Google Inc.
Software Engineer, PhD, Early Career, AI/Machine Learning, 2026 Start
Google Inc., Atlanta, Georgia, United States, 30383
Software Engineer, PhD, Early Career, AI/Machine Learning, 2026 Start
Apply to this position and have the opportunity to share your preferred working location from the following:
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 . PhD degree in Computer Science, ML/AI, or a related field, or equivalent practical experience. Experience in Machine Learning or Artificial Intelligence. Preferred 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 deep learning frameworks like TensorFlow/Jax/Pytorch. 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. Familiarity with model architectures (CNNs, NLP Transformers, Diffusion/Vision Transformers). Availability to start full-time role in 2026. 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. 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. 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. 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.
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Apply to this position and have the opportunity to share your preferred working location from the following:
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 . PhD degree in Computer Science, ML/AI, or a related field, or equivalent practical experience. Experience in Machine Learning or Artificial Intelligence. Preferred 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 deep learning frameworks like TensorFlow/Jax/Pytorch. 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. Familiarity with model architectures (CNNs, NLP Transformers, Diffusion/Vision Transformers). Availability to start full-time role in 2026. 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. 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. 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. 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.
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