Lead Machine Learning Engineer (AI)

Location: Hybrid in London, United Kingdom

Company

AI consultancy delivering responsible, human-centric AI solutions for government, finance, retail, energy, life sciences, and defence clients.

What you will do

• Set technical strategy, system architecture, and capability testing approaches for complex machine learning systems and Frontier AI models.
• Architect secure, production-grade ML software, orchestration tools, and scalable cloud infrastructure.
• Establish standards and best practices for safe, reliable, and ethical machine learning deployment at scale.
• Translate high-impact client needs into resilient AI solutions with cross-functional teams and executive stakeholders.
• Advise senior clients and partners on AI safety and technical strategy, communicating complex risks clearly.
• Mentor engineers and partner with Frontier Labs on safety evaluation, multi-agent tooling, and AI governance.

Requirements

• Significant leadership experience designing, deploying, and securing scalable LLM applications, multi-agent frameworks, and AI safety evaluation processes.
• Exceptional software engineering fundamentals and advanced Python expertise focused on resilient, enterprise-ready systems.
• Deep hands-on experience with AWS, Azure, or GCP; scalable cloud architectures; Docker; Kubernetes; agent sandboxing; and end-to-end cybersecurity.
• Mastery of the full ML lifecycle, with proven experience operationalising production systems using PyTorch, TensorFlow, or similar frameworks.
• Experience working autonomously in fast-paced, high-growth environments and guiding strategic technical decisions.
• Persuasive communication with technical teams and senior non-technical stakeholders, translating complex technical risks into clear strategic direction.

Culture & Benefits

• Hybrid work based in London.
• Inclusive, high-performing culture focused on intellectual curiosity, diversity, and measurable positive impact.
• Part-time hours may be discussed.
• AI tools may be used for research and interview preparation, but not to generate answers during live interviews.
• Interview note-taking uses Metaview, with an opt-out available.

Hiring process

• 30-minute Talent Team screen.
• 30-minute hiring manager introduction.
• 90-minute pair programming interview and 90-minute system design interview.
• 60-minute commercial and leadership interview.