Machine Learning Engineer — Production‑Grade AI Solutions

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

Benefits offered by this job

Unlimited Annual Leave Policy

Private healthcare and dental

Enhanced parental leave

Family-Friendly Flexibility & Flexible

Sanctus Coaching

Hybrid Working

Job summary

Faculty is hiring a Machine Learning Engineer to deliver bespoke, production‑grade ML solutions for diverse clients. You’ll bring ML out of the lab into real-world deployments, shaping scalable software architecture and best‑practice standards.

You will work with clients and cross‑functional teams to ensure technical feasibility and timely delivery of robust ML systems. Strong Python, cloud and container orchestration experience are required.

Qualifications

• Experience deploying production ML systems and pipelines.
• Strong Python software engineering practices.

Responsibilities

• Building and deploying production‑grade ML software, tools, and infrastructure.
• Creating reusable, scalable solutions that accelerate the delivery of ML systems.
• Collaborating with engineers, data scientists, and commercial leads to solve client challenges.
• Leading technical scoping and architectural decisions for project feasibility and impact.
• Defining and implementing Faculty’s standards for deploying ML at scale.
• Translating complex ML concepts for stakeholders as a technical advisor.

Skills

ML lifecycle

Python

Cloud platforms

Core ML concepts

Communication

Autonomy

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Faculty is hiring a Machine Learning Engineer to deliver bespoke, production‑grade ML solutions for diverse clients. You’ll bring ML out of the lab into real-world deployments, shaping scalable software architecture and best‑practice standards.

You will work with clients and cross‑functional teams to ensure technical feasibility and timely delivery of robust ML systems. Strong Python, cloud and container orchestration experience are required.