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Senior ML Platform & MLOps Engineer

ASOS

Greater London

Hybrid

GBP 80,000 - 100,000

Full time

Yesterday
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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.
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