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

Apply Now

Graduate Embedded Software Engineer

IC Resources
Cambridge
11 months ago
Applications closed

Related Jobs

View all jobs

Graduate: Sustainability Data Analyst

Graduate Data Scientist

Graduate Sustainability Data Analyst

Graduate Data Analyst - Power BI

Graduate Data Analyst - Power BI

Graduate Data Analyst - Power BI

Graduate Embedded Systems Engineer


Location:Cambridge


Salary:£35,000


We’re looking for a Graduate Embedded Systems Engineer to join a growing technology team specialising in software-defined radio (SDR) products. This role offers exposure to cutting-edge technologies, including embedded systems, digital signal processing (DSP), and mobile communications.


Graduate Embedded Systems Engineer Responsibilities:

  • Design and implement embedded software, primarily in C/C++.
  • Contribute to system designs and capture customer requirements.
  • Build tools for internal and customer use.
  • Test, debug, and resolve system issues.


Graduate Embedded Systems Engineer Qualifications and Skills:

  • A 2:1 degree or higher in Engineering (e.g., Electronics, Wireless Communications, Signal Processing, or Software Engineering).
  • Proficiency in at least one programming language, preferably C.
  • Strong problem-solving, communication, and time-management skills.
  • A passion for engineering and self-improvement.


Desirable Skills:

  • Knowledge of DSP, Verilog/VHDL, or mobile telephony systems (e.g., 5G, LTE, GSM).
  • Experience with Matlab.


If this Graduate Embedded Systems Engineer sounds of interest please reach out to Harry Hansford @ IC Resources.

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.