Production ML Engineer for Scalable AI Systems

Fdetimes; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

Faculty is seeking a Machine Learning Engineer to deliver bespoke, impactful AI solutions for diverse clients. You will bring ML from lab to production, shaping scalable software architecture and best practices while working with clients and cross-functional teams to ensure timely, high-quality delivery.

The role emphasizes operating models, collaboration, and the ability to translate complex ML concepts for stakeholders in a fast-paced environment.

Qualifications

• Experience with productionising ML models.
• Strong Python and software engineering practices.
• Cloud platforms and ML deployment experience.
• Excellent communication with stakeholders.

Responsibilities

• Build and deploy production-grade ML software, tools, and infrastructure.
• Create reusable, scalable solutions for ML delivery.
• Collaborate with engineers, data scientists, and commercial leads to solve client challenges.
• Lead technical scoping and architectural decisions for feasibility and impact.
• Define and implement standards for deploying ML at scale.
• Advise customers and partners on ML concepts and approaches.

Skills

ML lifecycle

Python

Cloud platforms

Docker & Kubernetes

Communication

System design

Tools

Scikit-learn

TensorFlow

PyTorch

Docker

Kubernetes

AWS

Azure

GCP

Job description

Faculty is seeking a Machine Learning Engineer to deliver bespoke, impactful AI solutions for diverse clients. You will bring ML from lab to production, shaping scalable software architecture and best practices while working with clients and cross-functional teams to ensure timely, high-quality delivery.

The role emphasizes operating models, collaboration, and the ability to translate complex ML concepts for stakeholders in a fast-paced environment.