FPGA Engineer

Harlow
1 year ago
Applications closed

Related Jobs

View all jobs

Senior RF Data Scientist / Research Engineer

Senior RF Data Scientist / Research Engineer

Become part of a dynamic group of FPGA engineers known for delivering advanced solutions across a wide array of domains, including space, aerospace, image processing, and machine learning. While their primary expertise is in FPGA design, they do perform some board design, focusing on pioneering FPGA technology innovations.

The team maintains strong partnerships with international collaborators and is frequently consulted by major FPGA manufacturers for advice and technical content.

Key Highlights:

Cutting-Edge Innovation: They lead key engineering projects involving space missions, advanced image processing, and machine learning, evidenced by repeat business with major space agencies reflecting their domain expertise.

Impactful Collaborations: Close collaboration with industry leaders like Xilinx has resulted in widely acknowledged and respected contributions.

Diverse Projects: Engagements range from lunar space station assignments to predictive maintenance on satellites, offering varied, challenging, and highly rewarding work.

Advanced Tools: Significant investment in cutting-edge tools and training ensures the team is equipped to excel.

About the Role:

As an FPGA Engineer, you will play a crucial role within the team, tasked with developing and verifying FPGA firmware. We seek not just a coder but a top professional capable of architecting solutions and devising robust verification strategies. Your contributions will be vital in transforming concepts into completed projects, consistently exceeding client expectations.

Responsibilities:

Develop and verify FPGA firmware, with an emphasis on solution architecture and verification strategy development.

Collaborate on stimulating projects, such as radar system verifications and machine learning applications for space missions.

Utilize your extensive expertise to achieve project milestones and deadlines while having the autonomy to implement innovative solutions.

Requirements:

Over 3 years of experience as an FPGA Engineer.

Proven ability to take key roles in projects, demonstrating significant technical proficiency and a hands-on approach.

Why Join Them?:

Join an experienced team with a strong industry presence.

Work on groundbreaking FPGA technology projects, contributing to endeavors like space missions and advanced image processing.

Benefit from a flexible work environment, typically requiring one day a week in the office, and opportunities for international collaboration

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 Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

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.