Requirements:

Bachelor's degree or equivalent practical experience
8 years of experience in software development and with data structures/algorithms
5 years of experience building and architecting large-scale, production quality Machine Learning (ML) systems
5 years of experience in distributed development and large-scale data processing
Experience coding in either C++ or Python
Experience with ML fundamentals, algorithms, and techniques, including supervised, unsupervised, and reinforcement learning, and experience in areas like natural language processing (NLP), computer vision, and generative AI

Nice to haves:

Experience with generative models (e.g., diffusion models, GANs, transformers) for various media formats (e.g., text, image, video, audio), including prompt engineering, fine-tuning, and evaluation techniques
Experience with RL algorithms and frameworks, including policy gradient methods, Q-learning, and actor-critic architectures
Experience building and leading high-performing research or engineering teams, fostering a positive and inclusive culture
Experience being published in ML/AI conferences or journals, demonstrating a strong research background, and ability to communicate complex technical concepts effectively
Familiarity with agent-based architectures, tool use, reinforcement learning, and techniques for evaluating and optimizing agent behavior

Build and lead a new team of ML engineers and researchers in London
Collaborate with Google Research and DeepMind to identify and prioritize emerging research areas
Conduct applied research on emerging ML/AI topics and drive the adoption of new AI technologies across Google products
Develop and evaluate ML models for pilot projects and scalable solutions
Develop a strategic roadmap for translating research into practical solutions