Senior Machine Learning Engineer (MLOps)

ASOS; Greater London; Hybrid; GBP 70,000 - GBP 90,000; Full time

Job summary

An online fashion retailer based in Greater London is seeking a Senior Machine Learning Engineer to design reusable ML templates and collaborate with product teams to enhance ML solutions. The role involves driving standardisation of workflows, enabling teams to productionise ML models, and implementing MLOps practices. The ideal candidate should have professional experience as a Machine Learning Engineer, strong skills in Azure technologies, Python, and familiarity with ML tools. Join a culture fostering creativity and growth.

Benefits

Employee discount

Personal development opportunities

Employee sample sales

LinkedIn learning materials access

25 days paid annual leave

Discretionary bonus scheme

Private medical care scheme

Flexible benefits allowance

Qualifications

• Professional experience as a Machine Learning Engineer, ideally with exposure to platform or infrastructure-focused work.
• Solid understanding of the end-to-end ML lifecycle, from experimentation through deployment and monitoring.
• Experience with ML Ops tools and practices such as MLflow, model registries, containerisation, and CI/CD pipelines.

Responsibilities

• Designing and developing shared ML engineering templates, tooling, and infrastructure.
• Driving standardisation and reusability of ML workflows across diverse product domains.
• Enabling teams to productionise ML models efficiently by providing best practices, templates, and technical support.

Skills

Machine Learning

Python

Azure Technologies

MLOps

Automation

Tools

Docker

Kubernetes

MLflow

TensorFlow

PyTorch

scikit-learn

XGBoost

Job description

As a Senior Machine Learning Engineer, you’ll focus on designing and implementing reusable ML templates, deployment patterns, and MLOps tooling that support scalable, reliable, and secure ML solutions across the organisation.

You’ll collaborate closely with ML Engineers and Scientists embedded in product teams such as Forecasting, Recommendations, Marketing, Customer, and Pricing helping them accelerate delivery and improve the quality of ML systems by providing a robust and standardised ML development experience.

What you’ll be doing:

• Designing and developing shared ML engineering templates, tooling, and infrastructure to support ML teams across ASOS.
• Driving standardisation and reusability of ML workflows, enabling consistency across diverse product domains.
• Enabling teams to productionise ML models efficiently by providing best practices, templates, and technical support.
• Implementing and promoting ML Ops principles including CI/CD for ML, model registries, monitoring, testing, and feature management.
• Collaborating with ML teams to understand pain points and evolve the platform accordingly.
• Partnering with Data Engineering, Platform Engineering, and Security teams to ensure scalable and cost-efficient ML infrastructure.

We believe being together in person helps us move faster, connect more deeply, and achieve more as a team. That’s why our approach to working together includes spending at least 2 days a week in the office. Its a rhythm that speeds up decision‑making, helps ASOSers learn from each other more quickly, and builds the kind of culture where people can grow, create, and succeed.

We’re ASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.

But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.

Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.

About You

• Professional experience as a Machine Learning Engineer, ideally with exposure to platform or infrastructure‑focused work.
• Strong experience working with ML Azure and other Azure technologies
• Solid understanding of the end‑to‑end ML lifecycle, from experimentation through deployment and monitoring.
• Proficiency in Python and familiarity with ML libraries like scikit‑learn, XGBoost, PyTorch or TensorFlow.
• Experience with ML Ops tools and practices such as MLflow, model registries, containerisation (Docker/Kubernetes), and CI/CD pipelines.
• Passionate about improving developer experience through automation, standardisation, and tooling.

BeneFITS

• Employee discount (hello ASOS discount!)
• ASOS Develops (personal development opportunities across the business)
• Employee sample sales
• Access to a huge range of LinkedIn learning materials
• 25 days paid annual leave + an extra celebration day for a special moment
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits