Senior ML Platform & MLOps Engineer

ASOS; Greater London; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading online fashion retailer is seeking a Senior Machine Learning Engineer to develop reusable ML templates and ensure efficient ML operations across the organization. You will collaborate with cross-functional teams, enabling best practices and standardised workflows while promoting CI/CD principles. Ideal candidates will have extensive experience in ML and proficiency in Python, along with familiarity with cloud solutions and ML Ops tools. This role offers a vibrant office culture requiring in-person collaboration at least two days a week.

Benefits

Employee discount

Personal development opportunities

Employee sample sales

Access to LinkedIn learning materials

25 days paid annual leave plus an extra day

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 and CI/CD pipelines.

Responsibilities

• Designing and developing shared ML engineering templates, tooling and infrastructure.
• Driving standardisation and reusability of ML workflows.
• Implementing and promoting ML Ops principles, including CI/CD for ML.

Skills

Machine Learning

Python

ML libraries (scikit-learn, XGBoost, PyTorch, TensorFlow)

ML Ops tools (MLflow, Docker, Kubernetes)

Cloud platforms (preferably Azure)

Distributed computing (Spark, Databricks)

Job description

A leading online fashion retailer is seeking a Senior Machine Learning Engineer to develop reusable ML templates and ensure efficient ML operations across the organization. You will collaborate with cross-functional teams, enabling best practices and standardised workflows while promoting CI/CD principles. Ideal candidates will have extensive experience in ML and proficiency in Python, along with familiarity with cloud solutions and ML Ops tools. This role offers a vibrant office culture requiring in-person collaboration at least two days a week.