Senior Machine Learning Engineer - Research

Cambridge University Press & Assessment
Cambridge
2 weeks ago
Create job alert
Closing Date: 29 March 2026

Salary: £64,490 - £86,255

Location: Cambridge - Triangle/Hybrid (2 days per week in the office) 

Contract: Permanent

Hours: Full Time (35 hours per week)
 
Shape the future of AI-powered learning solutions with Cambridge University Press & Assessment, a world-leading academic publisher and assessment organisation, and a proud part of the University of Cambridge.

This is an exciting opportunity for Machine Learning Research Engineers to join our innovative Applied AI team. You'll contribute to developing, deploying, and maintaining cutting-edge AI capabilities that drive the success of Cambridge English's products and services. 

About the Role 

As a Senior Machine Learning Research Engineer, you will play a pivotal role in driving innovation and advancing AI-powered solutions that enhance Cambridge English products. Your expertise will contribute to the continuous improvement of existing models and the development of cutting-edge technologies that address future business needs. 

Key Responsibilities: 

  • Technical lead in designing full-cycle AI solutions, including data collection and pipelines for reusable analysis, and monitoring and maintenance regimes for continuous development. 
  • Research, develop, deploy, and maintain scalable AI-powered solutions for Cambridge English products. 
  • Estimate time, cost and outcomes of technical solutions, and manage risks to ensure prompt delivery.
  • Collaborate with product, validation, and business teams to transform capabilities into impactful product features, while setting appropriate expectations.
  • Plan work and resources, including adoption of new tools, to ensure that the machine learning team stay at the forefront of AI and machine learning trends and position Cambridge as a leader in AI-driven. 
  • Mentor junior team members. 
 
About You 

To thrive in this role, you'll have a passion for AI-driven innovation and the ability to turn ideas into scalable solutions. 

Essential Qualifications & Skills: 

  • Master's degree (or equivalent qualification and experience) in machine learning or AI/computer science with substantial machine learning component.
  • Proven hands-on industry experience (minimum 5 years, not including internships) in designing, developing, and deploying machine learning solutions in production environments. 
  • Strong track record of successfully translating academic research into real-world applications and products. 
  • Ability to estimate suitability of candidate ML, NLP, LLM, and GenAI technologies for specific scenarios, estimate the time, cost and outcomes of different solutions, and apply effective risk management to ensure prompt delivery 
  • Deep experience in Python and PyTorch/TensorFlow. 
  • Industry experience in building scalable, production-grade AI services and automated data pipelines with tools like Docker, Kubernetes, and cloud platforms (e.g., AWS). 
  • Proven ability to collaborate effectively in Agile/Scrum teams and contribute to cross-functional projects. 
  • Exceptional communication skills for articulating complex technical concepts to both technical and non-technical stakeholders, translating business requirements into technical solutions. 
  • Proactiveness in communicating issues and suggesting solutions. 
  • Stay current with state-of-the-art research and applying emerging AI techniques to solve business problems. 
  • Ability to supervise a sub-team and mentor junior colleagues (can be developed on-the-job). 

Desirable: 

  • PhD degree or equivalent qualifications and experience in computer science, machine learning, artificial intelligence, or a closely related field. 
  • Experience in applying Natural Language Processing and/or Speech Technology techniques to solve real-world problems. 
  • Experience in applying machine learning to educational assessment and learning solutions 
  • Experience in leading research initiatives, contributing to patents, or publishing papers in machine learning or related AI fields. 
 

Rewards and benefits

We will support you to be at your best in work and to live well outside of it. In addition to competitive salaries, we offer a world-class, flexible rewards package, featuring family-friendly and planet-friendly benefits including:

  • 28 days annual leave plus bank holidays
  • Private medical and Permanent Health Insurance
  • Discretionary annual bonus
  • Group personal pension scheme
  • Life assurance up to 4 x annual salary
  • Green travel schemes
We are a hybrid working organisation, and we offer a range of flexible working options from day one. We expect most hybrid-working colleagues to spend 40-60% of their time at their dedicated office or location. We will also consider other work arrangements if you wish to work more flexibly or require adjustments due to a disability.

Ready to pursue your potential? Apply now. 

We review applications on an ongoing basis, with a closing date for all applications being 29 March although we may close it earlier if suitable candidates are identified. We'll set up interviews on a first-come, first-served basis.

Please note that successful applicants will be subject to satisfactory background checks including DBS due to working in a regulated industry.

Cambridge University Press & Assessment is an approved UK employer for the sponsorship of eligible roles and applicants under the Skilled Worker visa route. Please refer to the gov.uk website for guidance to understand your own eligibility based on the role you are applying for.

Why join us

Joining us is your opportunity to pursue potential. You'll belong to a collaborative team that's exploring new and better ways to serve students, teachers and researchers across the globe – for the benefit of individuals, society and the world. Sharing our mission will inspire your own growth, development and progress, in an environment which embraces difference, change and aspiration. 

Cambridge University Press & Assessment is committed to being a place where anyone can enjoy a successful career, where it's safe to speak up, and where we learn continuously to improve together. We welcome applications from all candidates, regardless of demographic characteristics (age, disability, educational attainment, ethnicity, gender, marital status, neurodiversity, religion, sex, gender identity and sexual identity), cultural, or social class/background.

We believe better outcomes come through diversity of thought, background and approach. We welcome applications from people from all backgrounds and communities, actively seeking to employ people from a wide range of different communities.

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer - Research

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

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.

Careers

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.

Jobs

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.

Careers Jobs

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.

🍪 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.