Machine Learning Engineer

About the Role

Our client is seeking a highly motivated and skilled Machine Learning Engineer to join their innovative data science team in Nottingham . This role is critical in bridging the gap between machine learning research and production-ready applications. You will be responsible for designing, building, deploying, and maintaining scalable machine learning models and systems. This hybrid position offers the chance to work on cutting-edge AI projects, collaborate with data scientists and software engineers, and enjoy a flexible work arrangement. You will contribute to developing intelligent solutions that drive significant business value and enhance our client's technological capabilities.

Key Responsibilities

• Develop, train, and deploy machine learning models for various applications, such as prediction, classification, and natural language processing.
• Build and maintain robust, scalable ML pipelines for data processing, model training, and inference.
• Collaborate with data scientists to optimize model performance and transition research models into production environments.
• Implement MLOps best practices, including versioning, monitoring, and automated testing of ML systems.
• Optimize machine learning code and infrastructure for performance and efficiency.

Requirements

• Master's or Ph.D. degree in Computer Science, Data Science, or a related quantitative field, or equivalent experience.
• 3+ years of professional experience in machine learning engineering or a similar role.
• Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Solid understanding of software engineering principles and best practices.

Benefits

• Competitive salary with performance-based bonuses.
• Comprehensive health, dental, and vision insurance.
• Generous budget for professional development, conferences, and further learning.
• Hybrid working model offering flexibility between office and remote work.
• Access to advanced computing resources and cutting-edge technologies.