Machine Learning Engineer

Faculty

full-time

Posted on: 9/17/2025

Origin: • 🇬🇧 United Kingdom

✨ AI Apply

Mid-LevelSenior

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchScikit-LearnTensorflow

About the role

Implementing data-driven approaches, contributing to the design of scalable software architectures, and ensuring best practices are followed throughout development.
Collaborate closely with our commercial team to help shape and deliver high-quality projects.
Contribute to defining the technical scope in early stages of client engagements, ensuring proposed solutions are feasible and aligned with business objectives.
Develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements.
Support both technical, and non-technical stakeholders, to deploy ML to solve real-world problems.
Building software and infrastructure that leverages Machine Learning.
Creating reusable, scalable tools to enable better delivery of ML systems.
Working with our customers to help understand their needs.
Working with data scientists and engineers to develop best practices and new technologies.
Implementing and developing Faculty’s view on what it means to operationalise ML software.
Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.
Working with senior engineers to scope projects and design systems.
Providing technical expertise to our customers.
Technical Delivery

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, GCP 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.
Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution