Full-Time Senior Machine Learning Engineer

• Designing and implementing end-to-end pipelines for model training, evaluation, and deployment.
• Automating a test framework for a suite of machine learning models. This may include:
  • Developing integration and regression tests for ML components and data pipelines.
  • Monitoring model performance and data drift using automated validation tools.
  • Building tools to simulate edge cases, production-like scenarios, and adversarial conditions.
  • Operationalising and benchmarking shadow deployments to validate challenger model performance. This includes defining criteria for model promotion or rollback.
• Contribute to the research and development of new use cases or extend challenger models.

• Has a strong foundation in statistics, proficiency in Python and common ML frameworks and experience working with cloud platforms and containerised environments.
• Has an in-depth understanding of ML lifecycle, from data preprocessing to deployment and monitoring.
• Strong commercial experience within a nimble team. Can deliver new technologies that have shown significant improvements in the speed at which new models are delivered.
• Can explain why a model is behaving the way it does and introduce challengers to account for these situations. Additionally, you can communicate the implications for the business/product.
• Communicates complex concepts clearly to both technical and non-technical stakeholders, articulating trade-offs and decision rationale.
• Has demonstrated extensive knowledge of ML system design, from feature engineering to model selection and performance optimisation.
• Can deploy rigorously tested challengers and define measurements of comparison with incumbents.

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