AI for Assessment Researcher

AQA
Manchester
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer - Research

Data Scientist

Data Engineer

Data Engineer

AI Engineer / Machine Learning Engineer

AI Data Analyst

AI For Assessment ResearcherManchester: £45,590 - £52,089Milton Keynes: £47,470 - £54,238Hybrid - 2x days a week in the officeImagine shaping the future of AI in education. What if your research could unlock innovative assessment that is fair, explainable, and high-quality? Join us in a pioneering project that merges advanced AI with educational assessment, making a real-world impact.At AQA, in collaboration with King's College London, we are developing a cutting-edge AI system to assist human experts in their work. You will be at the forefront of AI research, designing state-of-the-art algorithms with real-world applications.What You'll DoResearch, design, implement, and test NLP algorithms for AI-driven assessment.Collaborate with AQA assessment experts to ensure AI solutions align with real-world needs.Develop interactive front-end and back-end solutions to refine AI models with human feedback.Publish research findings, contribute to academic discussions, and present at conferences.What's in it for you?Enjoy a flexible work environment with a 35-hour week and extensive opportunities for professional and personal development.Access to an enhanced contributory pension scheme which could you see you paying in 7% and AQA contributing 11.5% (Other options are available)Receive 25 days of annual leave, increasing to 30 days with service, plus bank holidays and additional Christmas office closure.Comprehensive health coverage from day one, including Bupa PMI, Health Cash Plan, and Life Assurance.Participate in eco-friendly transport schemes, including electric vehicles and cycle-to-work options.What You'll NeedA PhD (or equivalent experience) in NLP, AI, or a related field.A strong research record, evidenced by publications or equivalent contributions.Proficiency in NLP techniques, research methodologies, and AI applications.The ability to communicate complex findings to technical and non-technical stakeholders.How do I apply?Read the full job description and upload your most recent CV and cover letter by following the link provided. As part of your application please also include an example of your previous work on NLP or AI (e.g. conference paper, github repository, jupyter notebook or similar).Closing date for applications will be Thursday 17th April.AQA is an equal opportunity employer committed to fostering an inclusive and diverse workplace where everyone-regardless of religion, ethnicity, gender identity or expression, age, disability, sexual orientation, or background-is valued, respected, and supported to thrive.#PRO22TPBN1_UKTJ

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 Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.