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Senior Software Engineer, Machine Learning, Gemini

Zurich, Switzerland (On-site)

Senior Software Engineer, Machine Learning, Gemini

1 Month ago • 3-5 Years • Artificial Intelligence • Research & Development

About the job

7 skills required for this role

Test your skills to join the top 1% applicants for this job

algorithms

reinforcement-learning

computer-vision

data-structures

model-deployment

networking

cross-functional

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 team is working on improving the accuracy and factuality of responses generated by Gemini, both standalone and in Retrieval Augmented Generation (RAG) settings. We iterate on the quality of RAG backends, and we build state-of-the-art language models through a variety of model training and optimization methods (e.g., Supervised Fine Tuning, Reinforcement Learning from Human Feedback). The team is also responsible for managing data quality, quality evaluation and quality monitoring. Gemini is a conversational AI tool that enables users to collaborate with generative AI and help augment their imagination, expand their curiosity, and enhance their productivity. Responsibilities: Leverage model training strategies like Supervised Fine Tuning (SFT) and preference-based approaches (e.g., Reinforcement Learning from Human Feedback, Identity Preference Optimization, etc.) to improve the quality of language models. Iterate on the Retrieval-Augmented-Generation (RAG) approaches to improve the accuracy of language model responses. Collaborate with cross-functional and Research teams on applying state-of-the-art machine learning approaches to LLM-based products.

Must have:

Bachelor’s degree or equivalent practical experience
5 years of experience with software development
3 years of experience testing, maintaining, or launching software products
1 year of experience with software design and architecture
3 years of experience with state-of-the-art GenAI techniques
3 years of experience with ML infrastructure

Good to have:

PhD in Machine Learning or a related field
Experience with training and optimizing large language models
Ability to grow under pressure in high-stakes, high-visibility environments

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Minimum qualifications:

Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
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 state-of-the-art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

PhD in Machine Learning or a related field.
Experience with training and optimizing large language models.
Ability to grow under pressure in high-stakes, high-visibility environments.

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.

Our team is working on improving the accuracy and factuality of responses generated by Gemini, both standalone and in Retrieval Augmented Generation (RAG) settings. We iterate on the quality of RAG backends, and we build state-of-the-art language models through a variety of model training and optimization methods (e.g., Supervised Fine Tuning, Reinforcement Learning from Human Feedback). The team is also responsible for managing data quality, quality evaluation and quality monitoring.

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

Responsibilities

Leverage model training strategies like Supervised Fine Tuning (SFT) and preference-based approaches (e.g., Reinforcement Learning from Human Feedback, Identity Preference Optimization, etc.) to improve the quality of language models.
Iterate on the Retrieval-Augmented-Generation (RAG) approaches to improve the accuracy of language model responses.
Collaborate with cross-functional and Research teams on applying state-of-the-art machine learning approaches to LLM-based products.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.