Principal Software Developer

Stoke Gifford
3 days ago
Create job alert

Principal Software Developer

The Role:

This is a highly varied role giving the successful candidate the opportunity to work across multiple projects and at all stages of the Software Development Lifecycle. Whilst focused on software development, this role also provides the opportunity to participate in software design at all levels. This will include work on:

Research & Development – Internally and externally funded research and development products investigating and developing low TRL technologies.
Product Development – Development and support of Synoptix products, primarily in the AI  and Computer Vision (object detection and track) domains.
Service Development – Development of Synoptix services, including our upcoming AI Assurance service offering.
Engineering Services – Delivery of engineering services on behalf of clients, assisting them in the development of their solutions.
Key Responsibilities:

Leading Software Development Projects

Act as part of a multidisciplinary team to develop products and services. This will include Systems Engineers, Security Engineers, Product Managers and others as required.
Support the wider team in project planning, requirements definition and requirements analysis.
Lead software design, development, testing, deployment and maintenance for a range of AI and Computer Vision products.
Providing Software Engineering Subject Matter (SME) Expertise

Act as part of multidisciplinary teams in delivering engineering services to Synoptix clients.
Provide SME guidance to Synoptix clients on the architecture and design of their software solutions.
Provide technical documentation, briefings and presentations to internal and external stakeholders at all levels of seniority.
Skills Required:

Essential:

Creative problem-solving skills
Strong proficiency in Python with experience in C++ development
Experience with Linux operating systems (e.g. Red Hat, Ubuntu)
Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP.
Experience with data analysis and manipulation tools (e.g. Pandas)
Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on:

Design(Architecting, High-Level Design and Low-Level Design)
Development
Testing
Deployment & Maintenance

Experience of using the Unified Modelling Language 
Excellent communication skills
Desirable:

Experience in the development of computer vision related products and services.
Experience with visual processing libraries; OpenCV, TensorFlow, PyTorch etc.
Experience operating as part of a multidisciplinary team
Experience developing and/or implementing reference architectures
Benefits:

Annual Company Bonus
25 Days holiday not including bank holidays with the option to buy/sell up to 5 days
Continuous professional development including incentives
Access to online Udemy training facility
Flexible working arrangements
Bike to work scheme
Electric car scheme
Private health care
Job well done scheme
Security Requirements:

Please note that due to the nature of our projects we can only accept sole UK national candidates who will need to be eligible to obtain UK Security Clearance

Related Jobs

View all jobs

Principal Engineering Lead (Data Products)

Principal MLOps Engineer - Chase UK (London)

Principal Data Engineer for Data Asset & Provisioning Technology

Principal MLOps Engineer - Chase UK

UNPAID VOLUNTEER - Technology Officers (Data Scientists/DevOps/Full Stack)

Principal Software Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Best UK Universities for Machine Learning Degrees (2025 Guide)

Explore ten UK universities that deliver world-class machine-learning degrees in 2025. Compare entry requirements, course content, research strength and industry links to find the programme that fits your goals. Machine learning (ML) has shifted from academic curiosity to the engine powering everything from personalised medicine to autonomous vehicles. UK universities have long been pioneers in the field, and their programmes now blend rigorous theory with hands-on practice on industrial-scale datasets. Below, we highlight ten institutions whose undergraduate or postgraduate pathways focus squarely on machine learning. League tables move each year, but these universities consistently excel in teaching, research and collaboration with industry.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.