Lead Machine Learning Engineer

About the Role

Our client is a pioneering force in AI and Emerging Technologies , actively seeking an experienced Lead Machine Learning Engineer to spearhead their remote R&D efforts. In this role, you will be instrumental in designing, building, and deploying advanced machine learning systems that address complex business challenges and drive innovation. Working entirely remotely, you will lead a talented team, foster a culture of technical excellence, and directly influence the strategic direction of our AI initiatives from anywhere in the UK . This is a unique opportunity to make a significant impact on cutting-edge technology while enjoying the flexibility of a fully remote position.

Key Responsibilities

• Lead the design, development, and deployment of scalable machine learning models and pipelines.
• Collaborate with product managers and data scientists to define project requirements and success metrics.
• Mentor and guide a team of machine learning engineers, fostering best practices and technical growth.
• Optimize ML systems for performance, reliability, and cost-effectiveness in cloud environments.
• Develop and maintain robust MLOps practices, including monitoring, testing, and CI/CD for ML workflows.
• Research and implement novel ML techniques to solve challenging problems.

Requirements

• MSc or PhD in Computer Science, Machine Learning, Data Science, or a related field.
• Extensive experience (5+ years) in machine learning engineering and production deployment.
• Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Strong understanding of data structures, algorithms, and software engineering principles.
• Proven ability to lead technical projects and mentor team members.

Benefits

• Highly competitive salary with performance-based incentives.
• Full remote working flexibility.
• Generous annual leave allowance.
• Comprehensive private healthcare coverage.
• Budget for professional development and continuous learning.