Software Engineer, Machine Learning, Gemini

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision.

• Master’s degree or PhD in Engineering, Computer Science, or a related 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 Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
• Experience developing, launching products, or technologies with LLMs.
• Demonstrated data analysis skills.

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.

A conversational AI tool that enables users to collaborate with generative AI and help augment their imagination, expand their curiosity, and enhance their productivity.

• Write product or system development code.
• Review code developed by other developers and provide feedback to ensure best practices (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.
• Work with research to understand SOTA technology and make adjustments/improvements to fit Gemini.
• Conduct in-depth data analysis to uncover insights, pinpoint opportunities, and inform the strategic development of a data flywheel.