Head of Hardware

Cambridge
8 months ago
Applications closed

Related Jobs

View all jobs

Head of Data, CDO, Data Governance, Professional Services, City London

Head of Data Architecture

Head of Business Intelligence

Head of Data, CDO, Data Governance, Professional Services, City London

Head of Data Analytics / AI

Head of Data Science

Head of Hardware – £80k - £120K - Cambridge

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.

  • FPGA design experience using Verilog.

  • Define and implement hardware architectures to optimise 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.

  • 4 years commercial Leadership experience

  • 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 job in Cambridge looks like a good fit for you, please apply today!

    For more information on this role or any other jobs across; FPGA, Mixed-signal, Electronics, Hardware, Embedded, C++ programming, Mechanical design, Analogue Eelctronics, 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.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.