Senior ML Engineer — Production-Grade AI for Finance

NLP PEOPLE; Milton Keynes; Hybrid; GBP 75,000 - 110,000; Full time

Benefits offered by this job

Unlimited Annual Leave

Private healthcare

Enhanced parental leave

Flexible working

Hybrid Working

Sanctus Coaching

Job summary

Faculty is seeking a Machine Learning Engineer to deliver bespoke AI solutions for Financial Services clients. You will bring ML from lab to production, contributing to scalable software architecture and best-practice deployment.

You will work with clients and cross-functional teams to ensure feasibility, timely delivery and high-quality, production-grade ML systems. Ideal candidates have hands-on experience with Python and ML frameworks, cloud platforms, and container orchestration.

Qualifications

• Understanding the full ML lifecycle and operationalising models.
• Strong Python skills and software engineering practices.
• Experience with cloud platforms and infrastructure (AWS/Azure/GCP).
• Hands-on with containerization and orchestration (Docker, Kubernetes).
• Clear communication with technical and non-technical stakeholders.

Responsibilities

• Build and deploy production-grade ML software and infrastructure.
• Create scalable ML solutions to accelerate delivery.
• Collaborate with engineers, data scientists and business leads.
• Lead technical scoping and architecture decisions for feasibility and impact.
• Define and implement standards for deploying ML at scale.

Skills

Python

ML lifecycle

Scikit-learn

TensorFlow

PyTorch

Cloud platforms

AWS

Azure

GCP

Docker

Kubernetes

Communication

Leadership

Education

Bachelor's or Master’s in CS/Math/Engineering

Tools

Docker

Kubernetes

Job description

Faculty is seeking a Machine Learning Engineer to deliver bespoke AI solutions for Financial Services clients. You will bring ML from lab to production, contributing to scalable software architecture and best-practice deployment.

You will work with clients and cross-functional teams to ensure feasibility, timely delivery and high-quality, production-grade ML systems. Ideal candidates have hands-on experience with Python and ML frameworks, cloud platforms, and container orchestration.