Machine Learning Engineer

About the Role

Our client is seeking a talented Machine Learning Engineer to join their dynamic data science team in Coventry . You will be responsible for developing, deploying, and maintaining machine learning models and systems that drive key business decisions and product innovation. This role is crucial for bridging the gap between theoretical ML research and practical, scalable application. You will work closely with data scientists, software engineers, and product managers to bring intelligent features to life, contributing to a forward-thinking organisation that values data-driven insights and technological advancement.

Key Responsibilities

• Design, build, and maintain production-level machine learning pipelines and infrastructure.
• Implement and fine-tune various ML models, including predictive, classification, and clustering algorithms.
• Collaborate with data scientists to deploy models into live production environments, ensuring scalability and reliability.
• Monitor model performance in production and implement strategies for retraining and improvement.
• Develop robust data processing and feature engineering techniques to support ML model development.
• Contribute to the team's best practices in ML engineering, code quality, and documentation.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.
• 2+ years of professional experience in machine learning engineering or software development with an ML focus.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, or scikit-learn.
• Experience with data processing frameworks (e.g., Spark, Pandas) and SQL.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Strong understanding of software engineering principles and version control systems (e.g., Git).

Benefits

• Competitive salary and annual bonus structure.
• Opportunity to work with large, impactful datasets and cutting-edge ML technologies.
• Comprehensive health, dental, and vision insurance.
• Pension scheme with employer contributions.
• Access to ongoing training and professional development resources.