Senior / Principal Firmware Engineer

Leonardo
Luton
2 years ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Simulation Engineer (Data Science)

Data Science Lead / Manager

Senior Machine Learning Engineer

Senior Data Scientist

Job Description:

Would like to deliver the complex Firmware that forms part of our self-protection systems installed on fast jet, UAV, land and naval platforms?

We have an exciting opportunity for an experienced Firmware Engineer to join our growing Luton based team. Within this role we can offer Custom or Hybrid working.

What you will do

As a Firmware engineer will work with the support of experts in their field, using world-class facilities to deliver Firmware for complex digital systems that meet challenging future customer requirements. Your role may even take you across the UK or abroad for technical reviews.

What we need from you

Design tools such as Xilinx, TCL, Verilog, System Verilog and UVM

FPGA architectures such as Xilinx 7. Xilinx UltraScale; Intel (Altera) or Microsemi (Actel).

Fast interfaces such as PCIe, Ethernet, and JESD is also required.

Auto-generated code using model driven engineering using Matlab and Simulink tools

Derivation of detailed Firmware requirements and architecture from system requirements

A structured approach to firmware design (RTCA DO-254 or similar)

Cryptography and anti-tamper techniques

Artificial Intelligence including machine learning and genetic algorithms

Electronics test methods and equipment

Good verbal and written communication skills

Working in mixed discipline teams 

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.

Security Clearance

:

Experience within the defence industry

Life at Leonardo

With a company funded benefits package, a commitment to learning and development, and a flexible approach to working hours focused on the needs of both our employees and customers, a career with Leonardo has never offered as many opportunities or been more accessible to as many people.

Flexible Working:Flexible hours with hybrid working options. For part time opportunities, please talk to us

Company funded flexible benefits:Access to private healthcare, dental schemes, Workplace ISA, Go Green Car Scheme, technology and lifestyle options (£500 annual allowance)

Holidays:25 days plus bank holidays, option to buy/sell leave and to accrue up to 12 additional flexi leave days per year

Pension:Award winning pension scheme (up to 10% employer contribution)

Wellbeing: Employee Assistance Programme with access to free mental health support, financial wellbeing support and network groups to demonstrate our ongoing commitment to diversity & inclusion (Enable, Pride, Equalise, Reservists, Carers)

Lifestyle:Discounted Gym membership, Cycle to work scheme

Training:Free access to more than 4000 online courses via Coursera

Referral Incentive:You can earn a reward for successfully referring a friend or family member

Bonus:Scheme in place for all employees at management level and below

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.