National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

AI Research Engineer, PhD

Cambridge
3 weeks ago
Create job alert

Job Title: AI Research Engineer
Location: Cambridge, UK
Salary: Competitive, depending on experience
Job Type: Full-time | Permanent
Department: Artificial Intelligence / Research & Development

Role Overview
We are looking for a talented and driven AI Research Engineer to join our growing team in Cambridge. This role is ideal for individuals with a strong foundation in machine learning or data science who are passionate about advancing AI technologies and applying them to real-world challenges. You will work on cutting-edge research and development projects, contributing to both theoretical innovation and practical deployment.

Education
Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, or a related technical field.
Minimum academic requirement: 2:1 or above in undergraduate degree and AAB or higher at A-level (or international equivalent).
We would consider data science backgrounds with relevant experience.
A degree from a globally recognized institution (Top 200 Global Universities) is required.
Required Skills and Qualifications
Strong analytical and problem-solving skills with a scientific approach to experimentation.
Proficiency in data science and machine learning workflows, including data handling, model training, and evaluation.
Solid understanding of software engineering practices, particularly in the context of ML development.
Hands-on experience with Python and ML libraries such as PyTorch, TensorFlow, and Scikit-learn.
Familiarity with tools like Git, Docker, and cloud platforms (e.g., AWS, GCP, Azure).
Qualifications (Preferred for Senior Roles)
Expertise in advanced ML areas such as Transformers, LLMs, NER, GANs, Reinforcement Learning, or Multimodal AI.
Academic or industry experience in fields like Natural Language Processing, Computer Vision, or Deep Learning.
For senior candidates, must have written publications in peer-reviewed journals or conferences (e.g., NeurIPS, ICML, ACL, CVPR).
Demonstrated impact in a commercial or applied research setting.
Experience mentoring junior engineers or leading research initiatives.

About Adecco:
Adecco operates as an Employment Agency and is an equal opportunities employer.
We are on the client's supplier list for this role.
Keywords
AI Research, Machine Learning Engineer, NLP, Computer Vision, Deep Learning, PyTorch, TensorFlow, LLMs, Transformers, GANs, Reinforcement Learning, Data Science, Python, Cambridge AI Jobs, Applied AI, Research Scientist, Artificial Intelligence, ML Research, AI Innovation

Related Jobs

View all jobs

Director of Data Analytics and AI (Basé à London)

AI Engineering Researcher

Quantitative Developer

Lead Data Scientist

Lead Data Scientist

Data Scientist, Data Intelligence, Professional Services GCR

National AI Awards 2025

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.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.

Part-Time Study Routes That Lead to Data Science Jobs: Evening Courses, Bootcamps & Online Masters

Data science sits at the intersection of statistics, programming and domain expertise—unearthing insights that drive business decisions, product innovation and research breakthroughs. In the UK, organisations from fintech and healthcare to retail and public sector are investing heavily in data-driven strategies, fuelling unprecedented demand for data scientists, machine learning engineers and analytics consultants. According to recent projections, data science roles will grow by over 40% in the next five years, offering lucrative salaries and varied career paths. Yet many professionals hesitate to leave their current jobs or pause personal commitments for full-time study. The good news? A vibrant ecosystem of part-time learning routes—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn data science while working. This comprehensive guide explores every pathway: foundational CPD units and short courses, hands-on bootcamps, accredited online MScs, plus funding options, planning strategies and a real-world case study. Whether you’re an analyst looking to formalise your skills, a software developer pivoting into data or a manager seeking to harness data-driven decision-making, you’ll find the right route to fit your schedule, budget and career goals.

The Ultimate Assessment-Centre Survival Guide for Data Science Jobs in the UK

Assessment centres for data science positions in the UK are designed to replicate the multifaceted challenges of real-world analytics teams. Employers combine psychometric assessments, coding tests, statistical reasoning exercises, group case studies and behavioural interviews to see how you interpret data, build models, communicate insights and collaborate under pressure. Whether you’re specialising in predictive modelling, NLP or computer vision, this guide provides a step-by-step roadmap to excel at every stage and secure your next data science role.