AI Engineering Researcher

Merton Park

9 months ago

Applications closed

Related Jobs

View all jobs

Senior MLOps Engineer

Machine Learning Researcher

Senior Machine Learning Engineer / Data Scientist

Research Scientist, Machine Learning

Geospatial Artificial Intelligence Research Scientist

Research Software Engineer: Geospatial Artificial Intelligence (Geo-AI)

Our client a London based Technology and Data Engineering leader have an opportunity in a high growth AI Lab for an ‘AI Engineering Researcher' A UK based 'Enterprise' Artificial Intelligence organisation, focussing on helping accelerate their clients journey towards becoming 'AI-Optimal' - starting with significantly enhancing its abilities in leveraging AI & machine intelligence to outperform traditional competition.
The firm builds upon its rapidly expanding research team of exceptional PhD computer scientists, software engineers, mathematicians & physicists, to use a unique multi-disciplinary approach to solving enterprise-AI problems.

Principal Activities of role: Data Pipeline Development:
• Design, develop, and maintain ETL processes to efficiently ingest data from various sources into data warehouses or data lakes.
• Data Integration and Management: Integrate data from disparate sources, ensuring data quality, consistency, and security across systems. Implement data governance practices and manage metadata.
• System Architecture: Design robust, scalable, and high-performance data architectures using cloud-based platforms (e.g., AWS, Google Cloud, Azure).
• Performance Optimization: Monitor, troubleshoot, and optimize data processing workflows to improve performance and reduce latency. Typical background:
− Bachelor’s or Master’s degree in computer science/engineering/Math/Physics, plus one or more of the following:
− Proficiency in programming languages such as Python, Java, or Scala.
− Strong experience with SQL and database technologies (incl. various Vector Stores and more traditional technologies e.g. MySQL, PostgreSQL, NoSQL databases).
− Hands-on experience with data tools and frameworks such as Hadoop, Spark, or Kafka - advantage
− Familiarity with data warehousing solutions and cloud data platforms.
− Background in building applications wrapped around AI/LLM/mathematical models
− Ability to scale up algorithms to production

Key Proposition: - This role offers the opportunity to be part of creating world-class engineered solutions within Artificial Intelligence / Machine Learning, with a steep learning curve and an unmatched research experience.

Time Commitments: 100% (average 40 hours per week)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

Industry Insights

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

Feb 9, 2026

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Feb 2, 2026

Jobs

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Jan 23, 2026

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.