Machine Learning Engineer deploying, automating, maintaining, and monitoring machine learning models within financial services. Collaborating in Agile teams to design and develop state-of-the-art ML products.
Responsibilities
Deploy, automate, maintain, and monitor machine learning models and algorithms in a production environment
Collaborate with colleagues to design and develop machine learning products
Codify and automate machine learning model production, including pipeline optimisation, tuning, and fault finding
Transform data science prototypes and apply appropriate machine learning algorithms and tools
Deploy and maintain end-to-end solutions, build metrics to improve system performance, and resolve data distribution differences affecting model performance
Understand business stakeholders' needs and create machine learning solutions to support business strategy
Produce machine learning models, including pipeline designs, development, testing, and deployment
Create frameworks for monitoring machine learning models in production environments
Deliver quality models and address any shortfalls through retraining
Lead and work in an Agile manner within multi-disciplinary data and analytics teams to achieve project outcomes.
Requirements
Academic background in a STEM discipline (Mathematics, Physics, Engineering, or Computer Science)
Experience with machine learning on large datasets
Understanding of machine learning approaches and algorithms
Experience of building, testing, supporting and deploying machine learning models into a production environment using modern CI/CD tools (TeamCity, CodeDeploy)
Good communication skills to engage with a wide range of stakeholders
Experience of coaching others
Knowledge of data science and machine learning
Experience of python programming with hands on experience with AI/ML both traditional ML and GenAI applications
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