Senior Software Developer

Cathcart Technology
Edinburgh
4 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Python Developer

AWS Backend Engineer (Inside IR35)

Principal Data Scientist

Software Engineer

Co-Founder / CTO Opportunity – AI Tech Recruitment Start-Up

Co-Founder / CTO Opportunity – AI Tech Recruitment Start-Up

A Scottish Med-Tech Org are looking for a skilled Senior / Software Developer (ideally with good Python experience) on a fully remote basis in the UK. Opportunity to with a modern tech stack, alongside some really strong Developers in a very rewarding environment.The company are well-established (they've been running for over 10 years) and have been going through a period of growth for the past few years now - they have recently brought in some really high-profile clients and are now recognised as one of the leaders in their field.Their development team currently works fully remote and they are offering this long-term (providing you are based in the UK - however they do have a preference for Scotland). Currently the Development team is roughly 40 strong, boasting Back-End, Front-End, Full Stack Developers, DevOps Engineers, Data Engineers and Product Managers - it's a really established environment.This role would involve joining a small squad of two, where you'll be tasked to develop an algorithm-based product for their client base. You'll largely be using Python , Azure and Kubernetes in this squad, so you'll ideally feel comfortable with most of those skills.They're an organisation that truly embody best practices (from TDD, BDD and DevOps), and each squad does have a strong focus on software security given the nature of the work - so Engineers that have worked in similar environments tend to get on really well here.Ideally, you'll have;** Good commercial experience with Python** Database Skills; SQL & NoSQL** Good Linux / Unix skills** Experience with cloud services (Azure, AWS or GCP)Experience with the following is highly desirable;** Docker / Kubernetes** Software Security** Working in a data driven environmentIn return the company are offering a competitive salary with good benefits (more than happy to discuss this in detail upfront) - also they offer 100% remote working from within the UK.If you think you're up to the challenge and enjoy working in a technically demanding, but yet really rewarding environment please apply and / or drop Douglas Paget at Cathcart Technology a message through Linkedin.TPBN1_UKTJ

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.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.