Senior ML Engineer: Production AI for National Security

Faculty; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Unlimited Annual Leave

Private healthcare and dental

Enhanced parental leave

Family-Friendly Flexibility & Flexible

Sanctus Coaching

Hybrid Working

Job summary

Faculty is seeking a Senior Machine Learning Engineer in the United Kingdom to lead development and deployment of scalable ML systems for diverse clients. You will design production-grade ML software and infrastructure, applying rigorous ethical and operational standards.

The role blends deep technical leadership with client-facing responsibilities. You will collaborate with cross-functional teams, mentor engineers, and help define best practices for deploying ML at scale, with occasional

Qualifications

• Experience operationalising models with TensorFlow or PyTorch.
• Strong Python and software engineering skills.
• Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Docker/Kubernetes).
• Excellent communication with technical and non-technical stakeholders.

Responsibilities

• Lead scoping and architecture for high-impact ML systems.
• Design and build production-grade ML software and scalable infrastructure.
• Define best practices for deploying ML at scale.
• Collaborate with engineers, data scientists, product managers, and business teams.
• Mentor junior engineers and shape engineering culture.

Skills

TensorFlow

PyTorch

Python

Cloud platforms

Docker

Kubernetes

Leadership

Stakeholder communication

Job description

Faculty is seeking a Senior Machine Learning Engineer in the United Kingdom to lead development and deployment of scalable ML systems for diverse clients. You will design production-grade ML software and infrastructure, applying rigorous ethical and operational standards.

The role blends deep technical leadership with client-facing responsibilities. You will collaborate with cross-functional teams, mentor engineers, and help define best practices for deploying ML at scale, with occasional