Scientific Software Developer

Job Posted: 1 May 2026

• Contract Term: Permanent
• Location: Shanklin, Isle of Wight
• Contract Type: Full time
• Salary: Competitive
• Industries: Engineering IT

The Role

We are seeking an engineer who bridges the gap between science and software. You will be responsible for translating complex numerical models and scientific concepts into robust, professional-grade software. While you must have a strong technical and scientific understanding, your primary role is a software engineer who champions modern development practices, clean code, and reliable deployment pipelines.

If you have 3 to 4 years of post-graduate experience and are passionate about building software that operates flawlessly in high-stakes security and nuclear environments, we want you on our team.

Responsiblities 

-          Algorithmic Development: Design, optimise, and implement complex numerical models and algorithms that process data from our radiation detectors and imaging devices.

-          Professional-Grade Engineering: Write clean, maintainable, and highly reliable code. Transform prototype scientific scripts into production-ready software.

-          Agile & DevOps: Champion modern software development approaches. Manage CI/CD pipelines, containerisation, and automated testing to ensure rigorous quality control.

-          Cross-Functional Collaboration: Work alongside physicists, hardware engineers, and front-end developers to integrate algorithms into the broader system architecture.

What We Are Looking For

Required

-          3–4 years of post-graduate commercial or research-based software engineering experience.

-          A strong academic foundation (degree in Computer Science, Physics, Applied Mathematics, or Engineering) combined with a genuine understanding of technical and scientific matters.

-        Proven ability to produce professional-grade software. You don't just write scripts; you build scalable, tested, and well-architected systems.

-         A solid grounding in Agile methodologies and DevOps practices (e.g., Git, Docker, CI/CD pipelines, automated testing).

Desirable 

-          Experience or background in imaging and computer vision

-          Familiarity with C++, Python, or similar languages heavily used in scientific computing.