Quality Assurance Engineer

London
4 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Quality Assurance and Test Automation Engineer

SC Cleared MLOps Engineer Job in Devon

Bioinformatic Software Engineer

Software Engineer (Junior)

Software Engineer (Junior)

GQA Artificial Intelligence Certification Lead

Quality Assurance Engineer - London - Up To £45,000

About the company:

Driven by a mission to reduce societal inequality through the effective use of data and insights, enabling better outcomes for vulnerable individuals. Their focus spans a range of areas, including Financial Inclusion, Homelessness, Adult Social Care, Children's Services, and Community Safety.

This is an exciting time to join as they are experiencing rapid growth. Their priorities include onboarding new clients, ensuring their platform remains robust and scalable, and developing innovative use cases. Primarily a technology provider, their projects are always geared towards achieving better outcomes for vulnerable residents and improving access to information for frontline staff.

They are seeking individuals who share their vision and are eager to contribute to the ambitious growth plans - 50% growth in 2025.

Location

Primarily remote, with occasional travel for team meetings in London. Office space is available in London for those who prefer to work on-site.

Responsibilities

Support the Testing team in implementing structured QA processes and methods
Ensure high quality standards are met within the software development lifecycle
Manually test all stages and development from internal project work and matching data, to the specification and acceptance criteria
Feedback all bugs, defects and failures collaboratively
Communicate effectively with team leads and project managers to provide feedback on client UAT findings
Support clients with UAT testingSkills and Experience

3yrs+ of experience as a manual QA Engineer
2yrs+ of experience with Azure DevOps
Strong skills in writing manual test scripts
Experience of multiple types of testing, including Regression, Smoke, Performance etc
Strong knowledge of software QA methodologies and processes
Ability to troubleshoot and solve technical problems
Ability to support PDMs with requirements and acceptance criteria
Ability to support clients with UAT
Strong analytical and problem-solving skills
Ability to manage time and prioritise tasks
Ability to work collaboratively across a cross-functional team including developers, project managers and data scientistsBenefits

Competitive salary reviewed annually.
Opportunity to work for a mission-driven company tackling societal challenges.
Flexible working hours focused on outcomes rather than time logged.
Remote working (excluding occasional team and client meetings).
Professional training and development opportunities.
25 days of annual leave, plus bank holidays.
Company pension scheme.
Private medical insurance.
Enhanced parental leave policies.
Cycle-to-work scheme.
Flu vaccinations, eye tests, and VDU glasses reimbursement.
Employee Assistance Programme, including access to mental health support, remote GP consultations, counselling, physiotherapy, and second medical opinions.If interested, please apply to share your CV

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.