Job description

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. The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives. The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . • Write product or system development code. • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality. • Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements. • Bachelor’s degree or equivalent practical experience. • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). • Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). Minimum qualifications: • Bachelor’s degree or equivalent practical experience. • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). • Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). Preferred qualifications: • Master's degree or PhD in Computer Science or related technical fields. • 2 years of experience with data structures and algorithms. • Experience developing accessible technologies. • Proven experience architecting, prototyping, and shipping complex ML systems from the ground up, with a deep understanding of machine learning and deep learning (e.g., Transformers, Diffusion, LLMs). • Demonstrated expertise in one or more of the following: generative models, segmentation algorithms, multi-modal fusion, spatio-temporal analysis.

Requirements

Must-haves

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Write product or system development code.
Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
2 years of experience with data structures and algorithms.

Nice-to-haves

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Master's degree or PhD in Computer Science or related technical fields.
Experience developing accessible technologies.
Proven experience architecting, prototyping, and shipping complex ML systems from the ground up, with a deep understanding of machine learning and deep learning (e.g., Transformers, Diffusion, LLMs).
Demonstrated expertise in one or more of the following: generative models, segmentation algorithms, multi-modal fusion, spatio-temporal analysis.

Application prep

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Keywords to mirror

mlmachine learning

Platform: google
Effort: medium

Benefits

Benefits detected in the listing.

Vision