Embedded Linux Software Engineer

Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Principal Data Scientist

Head of Data Science

Business Data Analyst

Lead Data Scientist

Head of Data Science

Embedded Linux Software Engineer
Bristol - remote & hybrid working
£45,000 to £60,000 + great benefits package

This is an excellent opportunity for an Embedded Software Engineer with strong Linux experience to join a rapidly growing company in a highly varied and interesting role where you can progress your career.

This company are leaders in energy saving technology. They are growing exponentially and through this growth are looking to add an Embedded Linux Engineer to their busy R&D team alongside electronics engineers, embedded software engineers, cloud engineers, web engineers and data scientists!

In this role you will support a varied development team working on bespoke hardware. This is a hybrid working role with two to three days a week required on site.

The ideal candidate will be an Embedded Software Engineer with experience of Linux, IoT and Perl.

This is a fantastic opportunity for an Embedded Linux Engineer to join a company that looks after its staff, rewards them well, and will allow you to progress your career.

The Role:
*Contribute to an established Perl codebase
*Assist in developing a next generation tech stack
*Work on software design, testing and integration with custom embedded devices
*Collaborate with cloud, electronics, and service teams to develop effective engineering solutions
*Hybrid working from Bristol and remote working available

The Person:
*Embedded software engineer with experience working in Linux environments
*Knowledge of IoT and internet security is beneficial
*Experience working with Perl, PHP, Linux, MQTT, LoRa (wireless), Modbus all beneficial
*Experience of Jira, Bitbucket, Jenkins, Google Workspace all beneficial
*Any experience with Golang, Docker, RabbitMQ is desirable but not a necessity

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 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.

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.