MLOps Lead Engineer (12 months) – Hyrbid – London

La Fosse Associates; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Job summary

La Fosse Associates, partnering with a UK heritage brand, is accelerating a large-scale AI and data transformation in London. The role leads MLOps maturity, setting foundations and standards to deliver ML at enterprise scale.

You'll drive model monitoring, governance and drift management, collaborating with business stakeholders and acting as the main link to external System Integrators. This is a 12-month hybrid contract in London.

Qualifications

• Extensive commercial experience in MLOps engineering.
• Strong Python development and engineering skills.
• Strong knowledge and working experience with Google Cloud Platform/GCP (essential), Azure; nice to have

Responsibilities

• Lead the maturation of the MLOps function and build the capability.
• Establish robust MLOps foundations, frameworks and engineering standards.
• Improve model monitoring, governance, reliability and scalability.
• Develop processes to manage model drift, model performance and operational health.
• Work closely with business stakeholders whose processes rely heavily on model accuracy.
• Act as the primary interface between internal teams and external Systems Integrators.

Skills

MLOps engineering

Python development

Tools

Google Cloud Platform (GCP)

Azure

Job description

12-Month Contract | Hybrid, London

2 stage interview, ASAP start

La Fosse is partnering with one of the UK’s most iconic heritage brands as it accelerates a large-scale AI and data transformation programme. Following significant investment and recent organisational change, there is a genuine appetite to modernise technology, improve data capabilities and scale machine learning across the business.

The organisation currently has multiple machine learning models operating in production, but recognises that it’s MLOps capability and supporting foundations are still relatively immature. This role has been created to provide the seniority, technical leadership and real-world experience required to establish best practice, improve operational maturity and ensure machine learning can be delivered reliably at enterprise scale.

Key Responsibilities

• Lead the maturation of the MLOps function and build the capability
• Establish robust MLOps foundations, frameworks and engineering standards.
• Improve model monitoring, governance, reliability and scalability.
• Develop processes to manage model drift, model performance and operational health.
• Work closely with business stakeholders whose processes rely heavily on model accuracy.
• Act as the primary interface between internal teams and external Systems Integrators.

Experience required

• Extensive commercial experience in MLOps engineering.
• Strong Python development and engineering skills.
• Strong knowledge and working experience with Google Cloud Platform/GCP (essential), Azure; nice to have
• Proven experience deploying and managing machine learning models in production environments.
• A track record of scaling MLOps capabilities within enterprise organisations

Why apply?

• Opportunity to shape the future of AI and machine learning within a household-name UK organisation.
• Significant investment and board-level support for transformation and innovation.
• Multi-year AI and modernisation roadmap