Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quality Assurance Engineer

SoCode
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Test Data Engineer

Test Data Engineer

Data Engineer

Data Engineer

Data Analyst / Engineer (Python)

Junior Data Engineer

The candidate should meet the following requirements Job Description Role Description The ideal candidate will haveQuality Assurance Engineer – 3 days on site in Cambridge
Are you interested in working for a tech company that are going from strength to strength? If you’re a QA Engineer with a Degree from a Top 200 Global University who has used tools like Cypress, Playwright and Cucumber, as well as having scripting experience in Python, JavaScript, Bash, etc. this is for you!
This machine learning company operate within the legal sector and are looking to scale massively throughout 2024 and into 2025 after a successful couple of years. They have a well-regarded product in the market and a client base to match this. Their product has been developed by industry-leading experts and is proven to be adding value to their clients by saving them time and money.
So, what will you be involved in?
Ensuring the software is working and behaving as it should under all circumstances. You’ll need an investigative mindset to ensure nothing is missed! Write tests validating the end-to-end functionalities of the product, with tools such as Cypress, Cucumber and Playwright. You’ll find and understand defects that occur and help in resolving them and extending the QA systems to prevent any future recurrence Bridge the gap between development and product teams; you’ll understand the specifications of the product and predicted behaviour and formalise these into testable units You’ll design and implement new metrics, measuring the quality of the releases and lead the transition of their engineering towards automation You’ll also work with Product teams and help them to expand their product spec documents If you’re a passionate Quality Engineer, with a thirst for learning and have the relevant experience, please hit apply!

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.