Senior Machine Learning Engineer

Salary: £45,000 - 83,000 per year

Requirements:

• 5+ years of experience as an MLOps / ML Engineer
• High proficiency in writing clear, production-ready Python code
• Experience with production ML models (online or offline) and standard MLOps practices
• Experience with monitoring and observability of production systems, with a strong sense of ownership
• Experience with training and operating models on Databricks
• Familiarity with cloud-based application development
• Familiarity with one or more ML frameworks and technologies such as scikit-learn, xgboost, TensorFlow, PyTorch, Spark, SageMaker, Vertex AI, Kubeflow, Seldon, or Triton
• Strong communication skills, able to express ideas clearly and collaborate across teams

Responsibilities:

• Build systems for training, deploying, and monitoring machine learning models used in our Disputes platform at scale
• Build and optimize data pipelines and backend services to process dispute and payment data in real time
• Build and scale our feature store for use cases both online and offline
• Take complete ownership of delivering comprehensive, end-to-end features within a startup-like setting, driving the entire lifecycle from requirement refinement and data pipeline construction to model training, troubleshooting, and production deployment
• Turn raw data into production-ready features that feed our dispute systems
• Collaborate with platform and backend engineers to integrate models seamlessly

Technologies:

• AI
• Backend
• Cloud
• Databricks
• Support
• Kubeflow
• Machine Learning
• MLOps
• Model Training
• PyTorch
• Python
• Spark
• TensorFlow
• AWS
• Azure

More:

Were Checkout.com, a global fintech company powering many of the digital experiences used every day, with more than 10 billion transactions processed yearly for over one billion global shoppers. Our Disputes ML team is building a brand-new, ML-driven dispute optimisation suite, offering a unique opportunity to work on an expanding area and make a tangible impact on millions of disputes. We value ownership, curiosity, and impact, and operate with 20 offices across six continents, with London as our HQ. We offer a hybrid working model with three days per week in the office, plus a culture built to support high performers through real ownership, fewer blockers, and meaningful challenges from day one.

last updated 35 week of 2026