Principal Machine Learning Engineer for Gemini at Google
vor 2 Wochen
Overview
Our team at Google focuses on enhancing the accuracy and factuality of responses generated by Gemini, both standalone and in Retrieval-Augmented-Generation (RAG) settings. We continuously iterate on the quality of RAG backends, aiming to build state-of-the-art language models through various training and optimization methods.
Key Responsibilities
- Develop and implement strategies for model training, such as Supervised Fine Tuning (SFT), to enhance language model quality.
- Collaborate on improving Retrieval-Augmented-Generation (RAG) approaches to achieve more accurate responses.
- Work on applying state-of-the-art machine learning techniques to LLM-based products, advancing the capabilities of Gemini.
Requirements
- Bachelor's degree or equivalent practical experience in software development.
- 5+ years of experience in software development, with a strong background in data structures and algorithms.
- 3+ years of experience in testing, maintaining, or launching software products, with a focus on software design and architecture.
- 3+ years of experience with state-of-the-art Generative AI techniques or related concepts.
- 3+ years of experience with ML infrastructure, including model deployment, evaluation, and optimization.
- PhD in Machine Learning or a related field (desired).
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