Lead Machine Learning Engineer - GenAI

Codesearch AI
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer

Senior Data Scientist

Machine Learning / Natural Language Processing Engineer (KTP Associate)

Lead Data Engineer

Head of Software Engineering | £180k – Java, Machine Learning and Data Driven

Lead Data Engineer

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

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 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.