DV Cleared AI Software Engineer – Production ML & Cloud

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

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.