Engineering Manager, MLOps, Marketplace, Ecommerce Users | Remote H

Engineering Manager, MLOps, Marketplace, Ecommerce

35 million users, UK Remote or London hybrid. Salary up to £140,000.

Our client is an extremely well‑known digital marketplace focused on sustainable ecommerce. With over 35 million active users globally, they’re redefining how people buy and sell second‑hand fashion, aiming to make the future of style both circular and accessible.

The company has offices in the UK, EU and US and has experienced significant growth especially around the US market, and now operates as part of a leading global e‑commerce group. They pride themselves on fostering inclusivity, creativity, and innovation and values that extend to both their community and their teams.

The organisation champions diversity, equal opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work‑life balance.

Our client is looking for an experienced MLOps Engineering Manager to lead and scale their MLOps function. You will shape how machine learning is developed, deployed, and scaled across the organisation.

This is a high‑impact role: you’ll lead a talented team of 6‑8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high‑performing ML systems that drive real‑world impact.

• Manage and develop a team of 8 MLOps engineers, fostering collaboration, high performance, and personal growth.
• Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy.
• Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management.
• Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs.
• Oversee system reliability, cost optimisation, and vendor relationships to keep infrastructure scalable and efficient.
• Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning.
• Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way.

• Proven experience leading an MLOps, ML Engineering, or Platform Engineering team.
• Solid background in applied machine learning and a passion for platform disciplines.
• Hands‑on experience with cloud platforms (AWS, GCP, or Azure), including large‑scale ML infrastructure management.
• Knowledge of GPU computing for model training and serving.
• Experience managing containerised workloads (Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, Git Hub Actions, Git Lab CI).
• Familiarity with distributed computing frameworks (Spark, Ray, Tensor Flow Distributed, PyTorch Distributed).
• Strong understanding of monitoring, logging, and observability for large‑scale ML systems.
• Experience in cost optimisation for compute/GPU workloads.
• Excellent people leadership and communication skills, able to influence technical and non‑technical stakeholders.
• Comfortable working in a fast‑paced, collaborative environment with strategic and operational responsibilities.
• Experience with vendor management and contract oversight.
• Familiarity with tools such as Databricks, Tecton (or Feast), Seldon, or Sage Maker.

• Private health and mental wellbeing coverage, including access to counselling and coaching.
• Salary up to £140,000 + Bonus & Benefits.
• 25 days annual leave, plus additional company‑wide rest days and volunteer leave.
• Flexible hybrid working, with the option to work abroad for limited periods.
• Generous parental, IVF, and carer leave policies.
• Learning and development budgets for conferences, mentorship, and skills growth.
• Pension matching, life insurance, and recognition for service milestones.

If you are interested in the Engineering Manager, MLOps, Marketplace, Ecommerce role, drop your CV and we will give you a call if we think you are a good fit.

Referrals increase your chances of interviewing at Owen Thomas by 2x.

• Mid‑senior level

• Full‑time

• Retail apparel and fashion