AI Software Engineer - DV Cleared

Searchability; City Of London; Hybrid; GBP 117,000 - 143,000; Full time

Job summary

Searchability, based in London, is seeking an AI Software Engineer with active UKSV DV clearance to join our hybrid team. You will build, deploy and scale production ML systems, focusing on Python software engineering, ML deployment, and cloud infrastructure in collaboration with engineers and data scientists.

You will drive production-ready ML solutions, across cloud platforms, using Docker and Kubernetes, and mentor stakeholders on technical approaches in a fast-paced environment.

Qualifications

• Strong Python development skills and software engineering practices.
• Experience taking ML models from development to production.
• Experience deploying ML models using Scikit-learn, TensorFlow or PyTorch.
• Hands-on experience with AWS, Azure or GCP.
• Experience with Docker and Kubernetes.
• Active UKSV DV clearance.
• Strong communication with non-technical stakeholders.

Responsibilities

• Build and deploy production-grade ML software, tools and infrastructure.
• Develop reusable, scalable solutions to accelerate ML deployment.
• Operationalise ML models across cloud platforms.
• Collaborate with software engineers, data scientists and stakeholders to solve client challenges.
• Advise customers on technical approaches and translate complex concepts for non-technical audiences.
• Define standards and best practices for deploying ML systems at scale.

Skills

Python

ML deployment

Docker

Kubernetes

Cloud platforms

Production ML

Communication

DV clearance

Tools

Scikit-learn

TensorFlow

PyTorch

Job description

AI Software Engineer – UKSV DV Cleared

NEW PERMANENT OPPORTUNITY AVAILABLE FOR AN AI SOFTWARE ENGINEER WITH DV CLEARANCE

• Salary: Up to £130,000
• Location: London
• Working Pattern: Hybrid
• Clearance: Active UKSV DV

I'm currently working with a leading AI organisation operating within the National Security space, who are looking for an experienced AI Software Engineer to join their team.

This is an opportunity to work on technically challenging projects, focusing on building, deploying and scaling machine learning systems in production environments.

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.

THE ROLE

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.

WHAT I'M LOOKING FOR

• 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.

THE OPPORTUNITY

You’ll join a team working at the intersection of software engineering and machine learning, helping bring ML systems into real-world use across critical client environments.

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.