Embedded Software Engineer

Southampton
10 months ago
Applications closed

Related Jobs

View all jobs

Digital and Technology Solutions Apprenticeship - Artificial Intelligence Software Engineering

Digital and Technology Solutions Apprenticeship - Artificial Intelligence Software Engineering

Senior Simulation Engineer (Data Science)

Machine Learning Engineer

Faculty Fellowship Programme - Data Science - May 2026

Audio Machine Learning Engineer

Embedded Software Engineer– Southampton - £45k - £55k – Semi Remote

Hexwired Recruitment has partnered with a world renowned Electronics manufacturer based in Southampton who are now seeking an Embedded Software Engineer to help develop and maintain a brand new system the company is developing.

The company are recognised globally, and are expanding because of a healthy order book. The company are now seeking an Embedded Software Engineer with excellent experience working on Linux and Embedded testing.

This is an Embedded Software role focusing on Processor design as well as comm interfaces. Due to the nature of the work, this will be a mostly onsite role with occasional remote working.

Key Requirements:

  • Bachelors, Masters or PhD in Computer science, Embedded Systems, Maths, Physics or similar

  • 2+ years commercial Embedded C experience

  • Good commercial Serial Comms experience (RS232, RS422, TCP/IP etc)

  • Experience working on Linux (Embedded Linux preferred but C on Linux also considered)

  • Any experience working on testing embedded code is highly desirable.

  • The ability to gain SC clearance is essential.

    The company are looking to offer circa £55k dependent on experience. Along with an excellent benefits package. If you’re interested in this Embedded Software role, please apply.

    For more information on this role, or any other jobs across; Embedded, C++ programming, Embedded Linux, Golang Development, Machine Learning, Data Science or Simulation contact us today

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.