Only 24h Left: Full Stack Python Developer

Eligo Recruitment
1 year ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer

Data Analyst

Data Analyst

Azure Data Engineer / BI Developer

Data Engineering Manager

Data Engineering Manager

Are you a Full Stack Developer who is looking for anew challenge? If the answer is yes, apply for the role today!BENEFITS: up to £70k basic salary, 10% discretionary annual bonus,25 days holiday plus bank holidays, pension, private healthcare,impressive training package, hybrid (ideally once a week, but noless than once a month) or full onsite at the office nearLeamington Spa You will be responsible in designing, developing andmaintaining an AI powered web-based EdTech application, workingwith a cross functional team. You will be a confident full stackdevelop utilising your Python and FastAPI back end skills,developing and integrating API's, and working with Azure servicesto deploy and manage the applications ensuring scalability andreliability. You will have a strong focus on UX and usability andbe able to create intuitive and visually appealing user interfacesand a strong experience with React. The company are a leadingprovider of EdTech solutions that uses AI, advanced naturallanguage processing and machine learning algorithms, they havebecome a trusted partner to the education sector and are embarkingon utilising the product within other compliance driven sectors.The team are dedicated to deliver reliable, high quality secureservices, and understand that in order to provide the best productpossible to their clients, the employees of the business are theirgreatest asset in achieving this. They look to empower their teamwith continuous learning and opportunities for career developmentinvesting heavily excellent training and personal development. Theyhave an office just outside Leamington Spa, but operate on aflexible working model giving staff the choice on whether to workhybrid or full onsite should they wish. Key Requirements -Commercial experience designing, developing and maintaining webbased applications - Full stack experience with Python and React -FastAPI - Ability to create intuitive and visually appealing UI -Strong focus on UX and usability - Good understanding of AzureServices for Deployment - Experience designing and implementingWebAPIs using RESTful Nice to have - Interest or experience with AIand Machine Learning - Experience with Microsoft Entra/ADintegration - Experience with React Native Interested? Please sendyour CV to Emma Stevens by applying to the role now.

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.