Machine Learning Engineer

Omnis Partners; England; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

A leading consultancy in the UK is seeking a hands-on Machine Learning Engineer for a contract role that focuses on supporting AI workspace integration for a global education organization. This mid-senior level position requires strong Python proficiency and experience in machine learning deployment, with a hybrid work model of 1-2 days per week onsite in London.

Qualifications

• Strong proficiency in Python with experience in machine learning deployment and MLOps tooling.
• Understanding of SharePoint and cloud‑based storage structures.
• Experience building document or knowledge management systems.
• Experience building document or knowledge management systems.
• Ability to work autonomously, taking ownership from design through to delivery.

Responsibilities

• Develop and maintain project‑specific workspace functionality.
• Implement UI integration with collapsible sidebar navigation.
• Build or integrate a cloud‑based file environment.
• Provide a pre‑defined library for initial deployment (e.g., finance or operational materials).
• Implement basic access controls, validation and testing.

Skills

Python proficiency

Machine learning deployment

MLOps tooling

Understanding of SharePoint

Strong Azure knowledge

Document management systems

Autonomous working ability

Tools

SharePoint

Azure

Job description

Associate Director - Data, Product and AI - Contract

📍 Location: Hybrid 1-2 days per week onsite in London

📅 Start: 24th November - 1 month initially but strong chance of extension

An established consultancy is seeking a Machine Learning Engineer (Contract) to support a global education organisation on an ongoing AI workspace project. The work will focus on extending internal tooling and integrating intelligent document management capabilities used across multiple regions.

This is a hands‑on individual contributor role, ideal for someone who enjoys working end‑to‑end from data and architecture through to deployment and knowledge transfer within a collaborative, agile delivery team.

Key Responsibilities

• Develop and maintain project‑specific workspace functionality, including file storage, metadata and system prompt management.
• UI integration with collapsible sidebar navigation.
• Build or integrate a SharePoint or cloud‑based file environment, including permissioned repositories for business units to upload and access documents independently.
• Provide a pre‑defined library for initial deployment (e.g., finance or operational materials).
• Implement basic access controls, validation and testing.

Skills & Experience

• Strong proficiency in Python with experience in machine learning deployment and MLOps tooling.
• Understanding of SharePoint.
• Strong Azure, or similar cloud‑based storage and directory structures.
• Experience building document or knowledge management systems.
• Ability to work autonomously, taking ownership from design through to delivery.

Seniority level

Mid‑Senior level

Employment type

Contract

Job function

Production

Industries: Business Consulting and Services and Education