Software Engineer - Medical Device

CT19
Oxford
2 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer

Software Engineer

Software Engineer

Software Engineer

Software Engineer

Software Engineer (Junior)

We are recruiting for an early-stage start-up based in Oxford who have recently secured their Seed funding. They are building a platform that leverages extensive Oxford University research in Raman Spectroscopy / Machine Learning to bring a disruptive technology allowing culture-free microbiology diagnostics in hours. The technology can identify bacteria and fungi from clinical samples and rapidly produce their antimicrobial profile in under 3 hours, compared to the current standard of 3 days. The success of this technology will ensure a revolution in the microbiology diagnostic space and set the standard for tomorrow.


This is a rare opportunity to join as one of the first employees on a mission to win against superbugs, we need the best and brightest to join us and enable this ambitious vision.


As an experienced Medical Device Software Engineer, you will take a hands-on role leading the development of the software for their initial prototype.


Job Title: Software Engineer – Medical Devices

Location: Oxford (Hybrid)

Salary: Highly Negotiable and Dependant on Experience


We are looking for a skilledFull-Stack Developerwith expertise inPythonto work on both front-end and back-end development of an innovative medical device. The ideal candidate will have experience working with medical devices in Python, and it would be a big bonus if they have worked with spectroscopy / imaging data.


Key Responsibilities:

  • Develop and maintain Software for both Back-End and Front-End.
  • Build and optimize APIs and backend services.
  • Integrate existing SDKs for hardware control / data acquisition from Raman spectroscopy systems.
  • Work with databases, ensuring efficient data storage and retrieval.
  • Collaborate with cross-functional teams to define and deliver new features.
  • Ensure high performance, security, and scalability of applications.
  • Testing and Debugging including unit / integration tests.
  • Collaborate with quality assurance teams to document processes in line with ISO13485.


Requirements:

  • Proficiency inPythonand relevant frameworks
  • Experience with frontend technologies (e.g., HTML, CSS, JavaScript, React).
  • Familiarity with cloud services (AWS, Azure, or GCP) is a plus.
  • Knowledge of version control systems like Git.
  • Familiarity with communication protocols such as USB, Serial, or Ethernet.
  • Ability to work in an agile environment and problem-solve effectively.


Please apply with an up to date CV for consideration.

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.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

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.