Principal Firmware Engineer

Luton
7 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Scientist and Machine Learning Researcher

Principal Data Science & AI Consultant — Clinical Analytics

Principal Machine Learning Engineer

Principal Machine Learning Engineer

Principal Data Science Consultant

Principal Machine Learning Engineer - Gameplay Agents

Principal Firmware Engineer

Luton

Paying up to £80p/h (Umbrella)

Responsibilities:

Artificial Intelligence including machine learning and genetic algorithms
Auto-generated code using model driven engineering using MATLAB and Simulink tools
Design tools such as Xilinx, TCL, Verilog, System Verilog and UVM
Derivation of detailed Firmware requirements and architecture from system requirements
A structured approach to firmware design (RTCA DO-254 or similar)

Experience required:

FPGA architectures such as Xilinx 7. Xilinx UltraScale; Intel (Altera) or Microsemi (Actel).
Fast interfaces such as PCIe, Ethernet, and JESD is also required.
Cryptography and anti-tamper techniques
Electronics test methods and equipment
HNC/HND or Undergraduate Degree (Electronic Engineering, Computer Science, AI, Games Programming, Physics, or Applied Physics) or you may just have lots of skills and experience gained through your hard work.
Due to the nature of our work, any candidate must have 5 years UK residency and be capable of achieving full SC security clearance.
Disclaimer:

This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change

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.