Machine Learning Engineer, Gemini Safety

You are an experienced Machine Learning Engineer with a strong engineering and research background who is excited about improving safety and alignment of the "Gemini" end-user product, delivering state-of-the art language models to our users. About us Artificial Intelligence could be one of humanity's most useful inventions. At Google DeepMind, we're a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority. The role Our team works on developing safe, aligned, and helpful Gemini models across all modalities (text, images, audio) as well as novel ways of evaluating them through superhuman autoraters or automated red teaming. To that end, we are advancing the state-of-the-art on the entire post-training pipeline. This includes innovations in RLHF/RL*F tailored to safety and alignment, novel and scalable ways of evaluating models to find weaknesses, as well as improvements in model understanding to guide future research. We are looking for a Senior Machine Learning Engineer excited to push the state of the art in these areas. Key responsibilities Apply and innovate on state-of-the-art modeling techniques with the goal of reducing safety violations while increasing human alignment using post-training approaches (e.g. SFT, RLHF/RL*F). Collaborate with peers and cross-functional research teams on applying state-of-the-art machine learning approaches to LLM-based products. Propose and quickly prototype novel ideas and implement advances in Gemini's production systems. Have bias for action: our team operates in a high-reward and fast-paced environment. In summary: we are looking for a Machine Learning Engineer with strong intuition and the ability to drive ambiguous projects end-to-end to push the boundaries of Safety and Alignment on LLMs. About you In order to set you up for success as a machine learning-focused software engineer at Google DeepMind, we look for the following skills and experience: MSc degree in computer science or machine learning or similar experience working in industry. 3+ years of experience with ML modeling and generative AI, working with data, model evaluations, and quality iterations. Proven knowledge and experience of Python, one or several machine learning frameworks (Jax, TensorFlow, or PyTorch), as well as algorithms and data structures. Ability to grow in high-stakes, high-visibility environments. In addition, the following would be an advantage: PhD in Machine Learning or a related field. Experience with training and optimizing large language models.

Artificial Intelligence could be one of humanity's most useful inventions. At Google DeepMind, we're a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.