Machine Learning Engineer

Faculty is seeking a Machine Learning Engineer to design, build, and deploy production-grade software and MLOps systems leveraging machine learning. This role involves supporting customers in solving high-impact problems, particularly within the Government & Public Services sector, potentially including National Security. The engineer will collaborate with data scientists and engineers to champion best practices, build reusable tools, and work with stakeholders to deploy ML solutions effectively. It's a dynamic role within a rapidly growing organization offering opportunities for growth and learning from brilliant minds.

Requirements

• Understanding of, and experience with the full machine learning lifecycle
• Working with Data Scientists to deploy trained machine learning models into production environments
• Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch
• Experience with software engineering best practices and developing applications in Python
• Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud providers (AWS, GPS or Azure)
• Demonstrable experience with containers and specifically Docker and Kubernetes
• An understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques
• Demonstrable experience of managing/mentoring more junior members of the team
• Outstanding verbal and written communication

Benefits

• Opportunity to learn from brilliant minds
• Professional challenge
• Dynamic role
• Autonomy and freedom to take ownership of problems