Senior ML Engineer: Safe AI & Production Systems

Faculty; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Faculty in the United Kingdom is seeking a Senior Machine Learning Engineer to lead development and deployment of cutting-edge AI systems for diverse clients. You’ll design, build and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards.

You’ll bridge AI research and real-world impact by architecting scalable ML systems, partnering with clients and cross-functional teams, mentoring engineers, and shaping our approach to practical

Qualifications

• Extensive experience building and deploying secure, scalable LLM applications.
• Proficient with TensorFlow or PyTorch and the full ML lifecycle.
• Strong Python engineering skills for robust, reusable systems.
• Experience with cloud platforms and end-to-end cybersecurity practices.
• Hands-on with container orchestration and production-grade ML infra.
• Ability to mentor engineers and communicate with stakeholders.

Responsibilities

• Lead technical scoping and architectural decisions for high-impact ML systems.
• Design and build production-grade ML software, tools, and scalable infrastructure.
• Define and implement best practices for deploying machine learning at scale across the business.
• Collaborate with engineers, data scientists, product managers and commercial teams to solve client challenges.
• Act as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies.
• Mentor and develop junior engineers, shaping the team’s engineering culture and depth.

Skills

LLM apps

Python

TensorFlow/PyTorch

Cloud platforms

Docker

Kubernetes

Cross-functional communication

Tools

AWS

Azure

GCP

Docker

Kubernetes

TensorFlow

PyTorch

Job description

Faculty in the United Kingdom is seeking a Senior Machine Learning Engineer to lead development and deployment of cutting-edge AI systems for diverse clients. You’ll design, build and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards.

You’ll bridge AI research and real-world impact by architecting scalable ML systems, partnering with clients and cross-functional teams, mentoring engineers, and shaping our approach to practical