Lead Machine Learning Engineer - GenAI

Codesearch AI
Glasgow
2 weeks ago
Create job alert

An unsolved problem in a multi-billion-pound industry


A cash positive, revenue generating start-up with signed commitments


An opportunity to lead the build of a first-of-its kind AI platform utilising SOTA tools and techniques


We are looking for a Lead Machine Learning Engineer – GenAI to build a field-changing, cutting-edge AI platform. In an industry filled with complexity and inefficiency, there’s an opportunity to create an intelligence platform that doesn’t only eliminate waste, but ultimately impacts people in key aspects of everyday life.


Our client is ahead of the curve and fully invested in taking their approach and vision to the next level.


What You’ll Be Doing


Building a multi-model, cutting edge intelligence platform integrating text and image data with state-of-the-art generative models, alongside traditional techniques


Designing a data and document ingestion strategy for multi-format data


Selecting the most appropriate models and approaches, RAG techniques and tools


Design and execute the technical roadmap and architecture to build a scalable platform


Develop and fine-tune LLMs and design multi-step Agentic workflows


Implement feedback loops for model performance evaluation


Provide input on and oversee the development of Robust LLMOps & DevOps practices


Lead and grow the ML team, mentoring and hiring engineers to scale the platform


80/20 split of hands-on work, weighted toward building


What You’ll Need


MSc or PhD in Machine Learning, AI, Computer Science or a related field (or equivalent experience)


Strong foundations in NLP with ideally a minimum of 5 years’ industry experience in AI, Machine

Learning, Reinforcement Learning or similar field


Have experience building and scaling AI-first products, with technical leadership experience, ideally in a start-up environment


Industry experience with LLMs (fine-tuning, optimising, performance evaluation) and Retrieval-


Augmented Generation (RAG) techniques including document linking.


Experience with knowledge graphs and vector databases


Strong experience with Python and modern AI development frameworks


Expertise in MLOps/LLMOps/DevOps including deploying AI solutions at scale.


Knowledge of traditional databases and scalable architecture design


Person - Whilst you’ll be working on cutting edge techniques, we are looking for people that build according to the need


You’ll build with urgency but be pragmatic in your approach


Location - Ideally this role is onsite in Dubai but we will consider remote working from the UK or Europe for the ideal candidate

Related Jobs

View all jobs

Lead Machine Learning Engineer - GenAI

Lead Machine Learning Engineer

Senior Machine Learning Engineer

Machine Learning Engineer (12-month FTC)

Lead Data Engineer

Lead Data Engineer

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.

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.

Navigating Data Science Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Data science has taken centre stage in the modern workplace. Organisations rely on data-driven insights to shape everything from product innovation and customer experience to operational efficiency and strategic planning. As a result, there is a growing need for skilled data scientists who can analyse large volumes of data, build predictive models, communicate findings effectively, and collaborate cross-functionally. If you are looking to accelerate your data science career—or even land your first role—attending data science career fairs can be a game-changer. Unlike traditional online applications, face-to-face interactions let you showcase your personality, passion, and communication skills in addition to your technical expertise. However, to stand out in a busy environment, you need a clear strategy: from polishing your personal pitch and asking thoughtful questions to following up with a memorable message. In this article, we’ll guide you through every step of making a strong impression at data science career fairs in the UK and beyond.

Common Pitfalls Data Science Job Seekers Face and How to Avoid Them

Data science has become a linchpin for decision-making and innovation across countless industries, from finance and healthcare to tech and retail. The demand for data scientists in the UK continues to climb, with businesses seeking professionals who can interpret complex datasets, build predictive models, and communicate actionable insights. Despite this high demand, the job market can be extremely competitive—and many applicants unknowingly fall into avoidable traps. Whether you’re an aspiring data scientist fresh out of university, a professional transitioning from a quantitative role, or a seasoned analyst looking to expand your skill set, it’s crucial to navigate your job search effectively. In this article, we explore the most common pitfalls data science job seekers face and provide pragmatic advice to help you stand out. By refining your CV, portfolio, interview strategies, and communication skills, you can significantly increase your chances of landing a rewarding data science role. If you’re looking for your next data science job in the UK, don’t forget to explore the listings at Data Science Jobs. Read on to discover how to avoid critical mistakes and position yourself for success.