Morson Talent | Principal Firmware Engineer | newcastle-upon-tyne, tyne and wear

Morson Talent
Edinburgh
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Principal Firmware Engineer (x2)

Location: Newcastle

Duration: 6 months

Rate: £51.32 per hour PAYE or £70 per hour Umbrella

As a Principal Firmware (FPGA) Engineer, you will create and develop firmware for leading edge airborne applications. You will be responsible for the design and development of Firmware designs using VHDL, for verifying designs using either VHDL or SystemVerilog and working to a structured firmware design process.

Proven Ability / Key Skills

  • Creating innovative VHDL based FPGA designs
  • Advanced verification techniques using either VHDL or SystemVerilog / UVM
  • Current FPGA technologies from either Xilinx, Altera or Microsemi and their tools
  • Model Driven Engineering tools including MATLAB and Simulink
  • High Speed Interface Design & Integration, including PCIe, DDR3, Ethernet
  • Analysing system level documents and deriving detailed Firmware requirements
  • Adopting a methodical approach to the full firmware design lifecycle, ideally working to a structured firmware process such as RTCA DO-254 or similar
  • Specifying complex timing and area constraints for efficient FPGA place and route
  • De-bugging firmware designs and supporting system related verification and integration

Additional

Due to the sensitive nature of the project involved all applicants must be capable of gaining a UK MOD Security Clearance to SC level.


JBRP1_UKTJ

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.