Python Developer

Yolk Recruitment Ltd
Cardiff
1 year ago
Applications closed

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Software Engineer - £100k - £120k - Fully Remote Are you ready to transform the landscape of business solutions for freelancers and SMEs in the UK? Join one of the fastest-growing fintech companies and be a part of a revolution. If you're a passionate software engineer, this is your chance to make a real impact while working fully remotely About the Company Our client is at the cutting edge of fintech innovation,that simplifies the lives of freelancers and small business owners. By integrating advanced AI technology with exceptional customer service, they empower users to focus on growing their businesses. Why Join? Innovative Environment : Be part of a team that's at the forefront of fintech innovation. Impactful Work : Help automate and simplify the tedious tasks small business owners face daily. Tech-Forward : Work with the latest tech and methodologies, deploying code to production up to 750 times a month. Diverse Team : Join a talented group of around 150 professionals, including software developers and data scientists. Trusted by Many : Over 100,000 customers rely on this service for their banking and administrative needs. The Tech Stack Infrastructure : Google Cloud Databases : Postgres (Cloud SQL, AlloyDB), MongoDB (Atlas) Messaging : RabbitMQ (CloudAMQP) Microservices : Kubernetes (GKE), mainly developed using modern async Python What We're Looking For Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field. Minimum of 5 years of professional software development experience, with a focus on building complex back-end systems. Technical Skills: Proven experience of building complex distributed backends in Python, or in one of the following programming languages and be ready to switch to Python: C#, C/C++, Go, Rust or Java. Knowledge of basic data structures and algorithms. Strong understanding of event-driven architecture: design/implementation of event-driven systems, addressing the challenges it brings. Solid concurrent programming experience. In-depth experience with Postgres (or with any other database): indexing issues resolution, concurrency control, fail-over mechanics, etc. Being a top individual contributor while effectively collaborating with teammates and fellow software engineers from other teams

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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.