Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building and deploying bespoke, production-grade AI solutions for public services with an accent on scalable software architecture and MLOps. Focus on operationalizing complex ML models, ensuring system feasibility, and driving measurable impact through human-centric AI applications.

Location: Hybrid, based in London, UK. Must be eligible for UK Security Clearance (SC) and willing to work on-site with clients.

Company

A leading AI research and deployment company focused on delivering human-centric, impactful AI solutions for global customers across government and private sectors.

What you will do

• Build and deploy production-grade ML software, tools, and infrastructure.
• Create reusable, scalable solutions to accelerate machine learning project delivery.
• Collaborate with engineers, data scientists, and commercial leads to solve complex client challenges.
• Lead technical scoping and architectural decisions to ensure long-term project success.
• Define and implement organization-wide standards for deploying machine learning at scale.
• Advise technical and non-technical stakeholders on complex ML concepts and system feasibility.

Requirements

• Experience operationalizing models using frameworks like Scikit-learn, TensorFlow, or PyTorch.
• Strong Python skills and extensive experience with software engineering best practices.
• Hands-on experience with cloud platforms (AWS, Azure, or GCP), including architecture and security.
• Proficiency with containerization and orchestration tools like Docker and Kubernetes.
• Strong understanding of core ML concepts including probability, statistics, and learning techniques.
• Must be eligible for UK Security Clearance (SC) and willing to travel to client sites.

Culture & Benefits

• Unlimited annual leave policy.
• Private healthcare and dental coverage.
• Enhanced parental leave.
• Family-friendly flexibility and hybrid working environment.
• Sanctus coaching and focus on mental well-being.

Hiring process

• Talent team screen (30 mins).
• Pair programming interview (90 mins).
• System design interview (90 mins).
• Commercial interview (60 mins).