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Browse Open JobsManager, Applied AI Engineering, DeepMind
Summary by AIEngineer.careers
Manager, Applied AI Engineering, DeepMind is a AI Engineering Manager role (full-time). with Google careers. in GREATER LONDON, GB. Imported listing (source: workvisajobs.co.uk). Apply on the employer's site (workvisajobs.co.uk).
Imported listing (source: workvisajobs.co.uk) · Apply on workvisajobs.co.uk
GREATER LONDON · GB
—
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from workvisajobs.co.uk
DeepMind is seeking a Manager for Applied AI Engineering to lead teams building industry-scale ML systems. The role involves overseeing model deployment, evaluation, and data processing, as well as driving generative AI and reinforcement learning projects. You will manage technical strategy, mentor engineers, and collaborate with research teams.
Responsibilities
- Lead and manage applied AI engineering teams, setting technical direction and priorities.
- Oversee development and optimization of ML infrastructure, including model deployment, evaluation, and data processing.
- Drive application of generative AI and reinforcement learning across products.
- Recruit, mentor, and manage engineers, fostering a high-performance culture.
Requirements
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
- 8 years of software development experience, including system design, data structures, and algorithms.
- 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure.
- 5 years of experience in a technical leadership role, with 5 years in people management or team leadership.
Google careers
Mountain View · US · 183103+ employees
Google is a global technology company known for its search engine, cloud computing, and various software and hardware products. It focuses on solving complex problems through technology, including artificial intelligence, machine learning, and consumer electronics.
