Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building and deploying production-grade machine learning software, tools, and infrastructure for high-stakes national security and AI safety projects with an accent on scalable architecture, model operationalisation, and responsible deployment. Focus on defining ML engineering standards, making architectural decisions, and translating complex machine learning concepts for technical and non-technical stakeholders.

Location: Hybrid role based in London, UK, with occasional onsite work at client locations. Eligibility for UK Developed Vetting (DV) may be required.

Company

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

What you will do

• Build and deploy production-grade machine learning software, tools, and infrastructure.
• Create reusable and scalable solutions that accelerate the delivery of ML systems.
• Collaborate with engineers, data scientists, and commercial leads to solve critical client challenges.
• Lead technical scoping and architectural decisions to ensure project feasibility and impact.
• Define and implement standards for deploying machine learning at scale.
• Advise customers and partners by translating complex ML concepts for stakeholders.

Requirements

• Experience across the full machine learning lifecycle, including operationalising models built with Scikit-learn, TensorFlow, or PyTorch.
• Strong Python skills and solid software engineering practices.
• Hands-on experience with cloud platforms and infrastructure such as AWS, Azure, or GCP, including architecture and security.
• Experience with Docker and Kubernetes for building and managing applications at scale.
• Understanding of probability, statistics, and common machine learning techniques.
• Excellent communication skills and the ability to advise non-technical stakeholders; eligibility for UK Developed Vetting may be required.

Culture & Benefits

• Hybrid working and flexible working arrangements.
• Unlimited annual leave policy.
• Private healthcare and dental coverage.
• Enhanced parental leave and family-friendly flexibility.
• Sanctus coaching.
• Part-time hours are open for discussion.

Hiring process

• Talent Team screen lasting 30 minutes.
• Pair programming interview lasting 90 minutes.
• System design interview lasting 90 minutes, followed by a 60-minute commercial interview.