Lead Architect — Generative AI & ML Infrastructure

Google DeepMind; Greater London; On-site; GBP 140,000 - 230,000; Full time

Job summary

Google DeepMind seeks a senior ML engineering leader to guide the development and deployment of generative AI applications. You will drive rapid feature development, collaborate with researchers and product managers, and scale products from concept to production.

You will mentor engineers, shape architecture, and push for high-impact AI innovations across teams. The role emphasizes translating AI research into real-world products, building robust software, and leading engineering teams in

Qualifications

• Bachelor's degree or equivalent practical experience in a related field.
• 8+ years software development experience including system design, data structures, and algorithms.
• 7+ years leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure.
• 5+ years in a technical leadership role with people management experience.

Responsibilities

• Lead the design, development, and deployment of scalable generative AI applications and advocate best practices.
• Drive rapid development of new features while mentoring team members to foster a high-performing environment.
• Collaborate with researchers and product managers to translate research into tangible product features.
• Oversee optimization of software performance and ensure reliability of deployed applications.
• Lead architecture and development of new products from 0 to 1.

Skills

Software architecture

ML design leadership

People management

Technical leadership

Project strategy

Education

Bachelor's degree or equivalent experience

Tools

TensorFlow

PyTorch

Hugging Face

Job description

Google DeepMind seeks a senior ML engineering leader to guide the development and deployment of generative AI applications. You will drive rapid feature development, collaborate with researchers and product managers, and scale products from concept to production.

You will mentor engineers, shape architecture, and push for high-impact AI innovations across teams. The role emphasizes translating AI research into real-world products, building robust software, and leading engineering teams in