Software Engineer, Machine Learning, Gemini

3 Months ago • 2 Years + • Artificial Intelligence

Job Summary

Job Description

Google is looking for a Software Engineer, Machine Learning, to join their Gemini team in Zürich, Switzerland. This role will involve collaborating with Research teams to understand technologies and integrate them into Gemini/Bard, leveraging Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), and Preference Optimization (IPO) to improve quality. The engineer will conduct data analysis to uncover insights and inform the strategic development of a data flywheel. This is a high-impact role with tremendous potential for growth and increased responsibility. The ideal candidate will have experience with Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), and Large Language Models (LLMs). They will also be comfortable working in high-pressure environments and have excellent data analysis skills.
Must have:
  • Bachelor’s degree in Computer Science or equivalent experience
  • 2 years of software development experience
  • 2 years of experience with data structures or algorithms
  • 2 years of experience with machine learning algorithms and tools
  • Experience with Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF)
  • Excellent data analysis skills
Good to have:
  • PhD in Machine Learning or a related field
  • Experience working with Large Language Models (LLMs)
  • Ability to work under pressure

Job Details

Minimum qualifications:

  • Bachelor’s degree in Computer Science, 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.
  • 2 years of experience with data structures or algorithms.
  • 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.

Preferred qualifications:

  • PhD in Machine Learning or a related field.
  • Experience with Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
  • Experience working with Large Language Models (LLMs).
  • Ability to grow under pressure in high-stakes, high-visibility environments.
  • Excellent data analysis skills.

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.

The team is working on all Multimodal efforts across Gemini. We launched image retrieval, image understanding and generation. This includes a significant amount of deep modeling such as Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), and Identity Preference Optimization (IPO) establishing data flywheel, etc. Part of the team is also involved in building necessary infrastructure and landing multimodal model capabilities and features.

In this role, you will have significant external impact, offering tremendous potential for growth and increased responsibility.

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

  • Collaborate with Research teams to understand technologies, adapting and integrating them into Gemini/Bard to drive continuous improvement.
  • Leverage Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), and Preference Optimization (IPO) to quality hill climb.
  • Conduct data analysis to uncover insights, pinpoint opportunities, and inform the strategic development of a data flywheel.

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About The Company

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.

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