Job Requirements
- Bachelor's degree or equivalent practical experience
- At least 8 years of experience in software development, with a focus on data structures and algorithms
- Minimum of 5 years of experience building and architecting large-scale, production-quality Machine Learning (ML) systems
- At least 5 years of experience in distributed development and large-scale data processing
- Proficiency in coding with C or Python
- Solid understanding of ML fundamentals, algorithms, and techniques, including supervised, unsupervised, and reinforcement learning, and experience in NLP, computer vision, and generative AI
Preferred Qualifications
- Experience with generative models such as diffusion models, GANs, and transformers for various media formats, including prompt engineering, fine-tuning, and evaluation
- Knowledge of RL algorithms and frameworks, including policy gradient methods, Q-learning, and actor-critic architectures
- Experience leading high-performing research or engineering teams and fostering an inclusive culture
- Published research in ML/AI conferences or journals, demonstrating strong communication of complex technical concepts
- Familiarity with agent-based architectures, tool use, reinforcement learning, and techniques for evaluating and optimizing agent behavior
About the Role
Google's software engineers develop innovative technologies that impact billions of users worldwide. Our products handle massive information at scale and extend beyond web search. We seek versatile engineers with fresh ideas across various domains, including information retrieval, distributed computing, system design, networking, data storage, security, AI, NLP, UI, and mobile development. As a software engineer, you will work on critical projects with opportunities to switch teams and projects as our business evolves.
The Domain Applied ML team within Core ML accelerates ML/AI adoption across Google by developing efficient solutions in areas like parameter tuning, multimodal modeling, media generation, LLMs, and recommender systems.
The ML, Systems, & Cloud AI (MSCA) organization manages the hardware, software, ML, and infrastructure for all Google services and Google Cloud, prioritizing security, efficiency, and reliability to shape the future of hyperscale computing, including Google Cloud's Vertex AI and Gemini models.
Responsibilities
- 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 promote adoption of new AI technologies within Google
- Develop and evaluate ML models for pilot projects and scalable solutions
- Create a strategic roadmap to translate research into practical applications
Google is an equal opportunity employer committed to creating a diverse and inclusive workforce. We value all applicants regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or related conditions. We also ensure compliance with legal requirements regarding criminal histories and other protected statuses. For more information, see Google's EEO Policy and related resources.
English proficiency is required for all roles to facilitate global collaboration. Please note, Google does not accept resumes from recruitment agencies and is not responsible for fees related to unsolicited resumes.