Machine Learning Engineer
Skills
DevopsAmazon Web ServicesAnalyticsDriftLarge Language ModelsModelingOptimization
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Hands-on experience taking ML models into production
- Strong software engineering fundamentals in production Python testing version control and code review
- Solid grasp of the full ML lifecycle including feature engineering model development evaluation and production failure modes
- Comfortable owning deployment and monitoring of models including CI/CD for ML
- Exposure to forecasting optimisation or recommendation systems
- Practical experience with modern data platforms such as Snowflake Databricks AWS or Azure
- Able to operate independently in a lean environment
- Experience with secure maintainable code and model review practices
Nice to have
- Retail and Commerce Media experience
- AdTech exposure
- MLOps familiarity
- LLM systems familiarity
- Lean team experience
Day to day
- Turn experimental machine learning models into dependable production systems within the Data function.
- Own the full ML lifecycle including feature engineering model development deployment and monitoring for forecasting optimisation and recommendation capabilities.
- Work closely with data scientists data engineers DevOps and infrastructure teams to build robust scalable and reproducible ML solutions.