Lead Machine Learning Engineer, Multimodality, Gemini

Snapshot

Spearhead the development and deployment of cutting-edge multimodal AI models for Gemini, directly shaping the future of how users interact with image, video, and audio content across Google's platforms. This role demands a deep understanding of SOTA research and the ability to translate it into scalable, production-ready solutions.

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

Join our team at the forefront of multimodal AI development, where you'll contribute to building cutting-edge capabilities for Gemini. Multimodality is a strategic priority for Google, aligned with industry-wide trends and the future of AI. We are working on driving SOTA research to production and delivering best in class image generation, image, video and screen understanding. This momentum continues as we focus on:

• Developing state-of-the-art multimodal Gemini models.
• Expanding capabilities to understand and generate images and videos
• Launching on all surfaces including web, mobile and AR/VR.

You'll leverage advanced techniques like fine-tuning, RL*F, and PolicyOptimization / PreferenceData to push the boundaries of multimodal AI as well as focusing on low latency scalable solutions.

Key responsibilities

• Collaborate closely with research teams to evaluate and drive SOTA multimodal technologies, adapting and optimizing them for scalable launches.
• Provide technical leadership in defining the strategic direction for multimodal model development, ensuring alignment with Google's broader AI goals.
• Lead the implementation of advanced techniques, including SFT, RL*F,  IPO/DPO, to drive significant quality improvements and achieve breakthrough performance in multimodal models.
• Independently design and execute complex experiments to validate and refine model architectures and training methodologies.
• Conduct rigorous, in-depth data analysis to identify critical insights, uncover emerging trends, and pinpoint strategic opportunities for enhancing multimodal capabilities.
• Develop and articulate data-driven recommendations that inform the strategic development of a robust data flywheel, driving continuous improvement and innovation.
• Act as a technical mentor to other team members.

About you

In order to set you up for success as a Lead ML Engineer at Google DeepMind, we look for the following skills and experience:

• Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
• Proven experience in developing and deploying large-scale machine learning models, particularly in the domain of multimodal AI (image, video, audio).
• Experience with large language models and multimodal model architectures.
• Strong problem-solving and analytical skills, with the ability to design and execute complex experiments.

In addition, the following would be an advantage: 

• PhD in ML or considerable experience working with LLMs
• Experience with SFT, RL*F, IPO/DPO.
• Strong data analysis skills
• Thrive under pressure in high-stakes, high-visibility environments.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Application deadline: 12pm GMT Thursday 10th April 2025 

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