Full-Time Senior Machine Learning Engineer

What the day to day will look like:

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.

We are looking for someone who:

• 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.

What is the last date for applying to the job?

Which countries are accepted for this remote job?