Python Developer

Yolk Recruitment
Grangetown
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 PythonWhat 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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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.