AI Software Engineer - DV Cleared

The role is heavily focused on Python software engineering, ML deployment and cloud infrastructure, working alongside engineers, data scientists and technical stakeholders to deliver robust, production-grade solutions for complex client challenges., You’ll play a key role in taking machine learning models from development into production, building the software, tools and infrastructure required to deploy and operate ML systems reliably at scale.

Working across software engineering, cloud architecture and machine learning operations, you’ll help develop reusable solutions, influence technical decisions and establish best practices for deploying machine learning in production environments.

You’ll also work directly with clients and cross-functional teams, helping shape technical solutions, assess feasibility and ensure successful delivery.

WHAT YOU’LL BE DOING

• Building and deploying production-grade machine learning software, tools and infrastructure.
• Developing reusable, scalable solutions to accelerate the delivery of ML systems.
• Operationalising machine learning models built using frameworks such as Scikit-learn, TensorFlow or PyTorch.
• Working across cloud platforms and infrastructure, including architecture and security considerations.
• Using Docker and Kubernetes to build, deploy and manage applications at scale.
• Contributing to technical scoping, software architecture and engineering best practices.
• Collaborating with software engineers, data scientists and commercial teams to solve complex client challenges.
• Advising customers and partners on technical approaches, translating complex concepts for non-technical stakeholders.
• Helping define standards and best practices for deploying machine learning systems at scale.

• Strong Python development skills and a solid understanding of software engineering best practices.
• Experience taking machine learning models from development through to production.
• Understanding of the full machine learning lifecycle and experience operationalising models built with frameworks such as Scikit-learn, TensorFlow or PyTorch.
• Hands-on experience with cloud platforms such as AWS, Azure or GCP, including infrastructure, architecture and security.
• Experience with Docker and Kubernetes.
• A sound understanding of core machine learning concepts, including probability, statistics and common learning techniques.
• Strong communication skills, with the ability to advise technical teams and engage confidently with non-technical stakeholders.
• The ability to take ownership of technical scope, make informed decisions and deliver solutions in a fast-paced environment.
• Active UKSV DV clearance., This is a strong opportunity for a software engineer with hands-on ML deployment experience who enjoys solving complex technical problems, building scalable infrastructure and taking ownership of production-grade solutions.