Python Software Engineer

Godstow
11 months ago
Applications closed

Related Jobs

View all jobs

Senior AI Engineer | GenAI | Information Retrieval | ML | NLP | Hybrid London | Up to £130k

Senior AI Engineer | GenAI | Information Retrieval | ML | NLP | Hybrid London | Up to £130k

Python & Kubernetes Data Engineer – AI/ML & Analytics

Python & Kubernetes Data Engineer for AI/ML Workflows

Senior Software & Data Engineer (Java/Python)

Data Engineer III - Python, Databricks & AWS

Python Software Engineer – Data-Driven Innovation in Infrastructure

A pioneering technology company is looking for a Python Software Engineer to develop advanced analytical solutions for real-world engineering challenges. This role is perfect for someone passionate about using programming, data science, and cutting-edge algorithms to improve infrastructure monitoring and decision-making.

The Role:

This position involves designing and implementing data processing techniques for complex datasets, integrating various sources of remote sensing information. The successful candidate will play a key role in developing computational tools that extract meaningful insights, ultimately supporting critical projects in the transport and construction sectors.

Key Responsibilities:

Develop algorithms to process and analyze complex geospatial and sensor data.
Work with large-scale datasets to drive insights and support machine learning applications.
Improve internal software tools using Python and other relevant technologies.
Collaborate with a team of scientists and engineers to solve industry-specific problems.
Present research findings and contribute to ongoing technical discussions.

Ideal Candidate:

Strong programming skills, particularly in Python.
Background in data science, mathematics, engineering, or a related field.
Experience with signal, image processing & data science techniques.
Interest in applying computational techniques to real-world infrastructure challenges.
This is an exciting opportunity to join a team at the forefront of data-driven engineering solutions. If you thrive on solving complex problems and want to apply your expertise to meaningful, high-impact work, this could be the perfect next step in your career

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.