Machine Learning Engineer

About the Role

Our client is looking for a talented and motivated Machine Learning Engineer to join their growing data science team in Leeds . In this role, you will be responsible for developing, deploying, and maintaining machine learning models that power innovative products and services. You will work closely with data scientists and software engineers to build scalable and efficient ML pipelines, ensuring that models are robust and performant in production environments. This hybrid role offers a balance of collaborative office work and remote flexibility, supporting a culture that values continuous learning and practical application of AI.

Key Responsibilities

• Develop and implement machine learning models using Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Build and maintain scalable ML pipelines for data preprocessing, model training, and deployment.
• Deploy ML models into production environments, ensuring they meet performance and reliability requirements.
• Monitor model performance in production, identify drift, and implement retraining strategies.
• Collaborate with data scientists to prototype and validate new ML algorithms and techniques.
• Contribute to the design and implementation of data infrastructure supporting ML workflows.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, or a related quantitative field.
• 3+ years of experience as a Machine Learning Engineer or in a similar role.
• Strong programming skills in Python and experience with ML frameworks.
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Understanding of MLOps principles and best practices for model deployment and monitoring.
• Good problem-solving skills and ability to work effectively in a team.

Benefits

• Competitive salary and performance bonuses.
• Hybrid working model offering flexibility.
• Comprehensive health insurance package.
• Generous annual leave allowance.
• Access to training and development resources in Leeds .