Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Head Of Hardware

Cambridge
10 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering - Preston

Head of Data Engineering - Preston

Hexwired have partnered with an exciting low latency electronics manufacturer in Cambridge who are looking for someone to head up their hardware team. They are looking for someone with 10+ years of experience in FPGA, digital and low-latency system development to take a hands on role in leading their Hardware development.

Key Responsibilities:

  • Provide technical leadership and strategic guidance to the hardware engineering team.

  • Lead the design and deployment of advanced FPGA platforms for low-latency trading systems.

  • Collaborate with technical leadership to align hardware initiatives with business goals.

  • Define and implement hardware architectures to optimize system performance and scalability.

    Required Skills and Expertise:

  • Advanced degree in Electronics Engineering, Computer Engineering, or a related field.

  • Over 10 years of experience in FPGA design and digital logic for low-latency systems.

  • Expertise in micro-architecture definition, RTL coding, and hardware verification.

  • Strong skills in simulation, synthesis, timing analysis, and hardware emulation.

  • Proficiency with System Verilog and tools for Xilinx FPGA design.

  • Experience with programming languages such as C++, Rust, and Python.

    This exciting company is offering their prospective Head of Hardware £120K plus a strong benefits package. If this Head of Hardware role looks like a good fit for you, apply today!

    For more information on this role or any other jobs across; FPGA, Mixed-Signal, Electronics, Hardware, 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.

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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.