Hardware Engineering Lead - Up to £85,000

Humand Talent
Basingstoke
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Data Scientist Research Engineer

Product Manager - Machine Learning

Audio Machine Learning Engineer

Audio Machine Learning Engineer

Computer Vision Engineer

Hardware Engineering Lead: Join a Pioneering Team in Cutting-Edge Technology Are you passionate about driving innovation in Hardware engineering? Ready to lead a multidisciplinary team on ground-breaking projects? We’re looking for a Hardware Engineering Lead who can bring technical mastery and leadership to an exciting, dynamic team. Why This Role is Great: End-to-End Ownership : Youll oversee the complete system lifecycle, from conceptual design to the final product. Get ready to steer hardware and software integration for advanced systems. Cutting-Edge Projects : You’ll work on advanced technologies that shape the future, including embedded Linux, custom hardware, and network solutions. Dive into everything from low-level device drivers to custom OS builds. Cross-Disciplinary Collaboration : You’ll collaborate with experts from electrical, mechanical, software, and algorithms teams—bringing holistic solutions to life. Innovation-Driven : This role encourages creativity. You’ll have the opportunity to explore novel solutions, work The Wishlist: We’re looking for someone who brings a unique mix of experience. If you have some of these skills, we’d love to hear from you: Team leadership with a knack for inspiring innovation Strong C/C++ programming and shell scripting skills Experience in embedded Linux environments, including Yocto and Buildroot Familiarity with network hardware and software stacks (4G/5G modems, VPNs, IPsec) Experience with CI/CD, automated testing, and version control tools (Git, SVN) A drive to innovate and push the boundaries of system engineering Why Apply? Lead a Talented Team : Guide and mentor engineers while staying hands-on with some of the most exciting tech in the industry. Shape the Future : You’ll play a key role in defining the product roadmap and driving the engineering strategy forward. Professional Growth : With a mix of leadership and hands-on work, this role provides a perfect balance for developing your career in both technical and managerial directions. Global Impact : Be part of projects that matter—your work will power solutions used worldwide. Salary up to £85,000 (flexible) Profit Share Scheme Work on a global scale So, if you’re looking for a new challenge at a well established tech driven company, who are ready to take things to the next level, please don’t hesitate to apply Keywords: Hardware Engineering, Software Engineering, Hardware Engineering, Embedded Systems, Firmware Development, System Integration, Network Protocols, Cyber-Physical Systems, Real-time Operating Systems (RTOS), Sensor Networks, Microcontroller/Microprocessor Systems, Cloud Computing, Edge Computing, Wireless Communication, Device Management, Requirements Engineering, Testing and Validation, Reliability Engineering, Scalability, Security Engineering, Data Analytics, Machine Learning, Agile Development, Prototyping, Simulation and Modeling, Power Management, Signal Processing.

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.