Senior Electronics Engineer

Orion Electrotech Sales
Leeds
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist (Applied AI)

Artificial Intelligence / Machine Learning Engineer

Senior Machine Learning Engineer

Senior Data Engineer

Senior Data Engineer - Energy

Senior RF Data Scientist / Research Engineer

Senior/ Principal Electronics Engineer

Are you an experienced Electronics Engineer with a passion for leading cutting-edge projects? We are offering an exciting opportunity to take a senior position within an expanding company specializing in advanced electronic systems. As a Senior Electronics Engineer, you will lead multi-disciplinary teams, provide technical expertise, and drive innovation across the business.

What Youll Do as a Senior Electronics Engineer:

  • Lead the design and development of electronics, including circuit design, PCB technology, power management, and processor interfacing.
  • Provide technical leadership in areas such as EMC, servo control, and signal transmission, and play a key role in shaping system architecture.
  • Act as a subject matter expert, offering strategic insights into project planning, resource management, and technology development.
  • Drive innovation by reviewing and improving engineering processes within the department.
  • Manage multi-disciplined engineering projects, from concept to delivery, with a focus on developing robust, resilient systems for diverse environments.
  • Lead, mentor, and support other engineers, fostering a culture of continuous learning and development.

What Were Looking For in a Senior Electronics Engineer:

  • A degree in Electronics or a related field, with accreditation from the IET and ideally over 6 years of relevant experience.
  • Strong theoretical and practical understanding of electronic design, including circuit emulation, power budgets, and performance analysis.
  • Proven leadership in managing both projects and people, with a focus on fostering innovation and best practices.
  • Expertise in embedded software design (ARM/KEIL) and experience working with EMC to military standards.
  • Familiarity with PCB design tools (e.g., Altium, OrCAD), and analysis tools (e.g., Python, Matlab, LT-Spice).
  • Knowledge of motors, drive technology, control systems, and performance analysis.
  • A Chartered Engineer or working towards Chartership is highly desirable.

What We Offer:

  • Flexible hybrid working arrangements with a 37.5-hour working week and Friday lunchtime finishes.
  • 28 days annual leave with a holiday purchasing scheme and Christmas closure.
  • A comprehensive benefits package including pension contributions, life assurance, income protection, and access to wellbeing services.
  • Opportunities for professional growth through ongoing learning and development.
  • A dynamic work environment with regular sports and social activities, gym discounts, and a rewards platform.

Security Clearance:Due to the nature of our work, candidates must be able to meet UK Security Clearance requirements, including proof of identity, employment history, and UK residency for the last five years.

If this role sounds of interest please get in touch with Bella from Orion or click APPLY NOW!


JBRP1_UKTJ

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 Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

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.