Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Data Scientist - Remote

Exposed Solutions
Penicuik
2 days ago
Create job alert

Our client is building the most advanced AI platform in their market. They help their clients serve customers with unmatched speed and accuracy.


They’ve invested heavily into building the ML stack, partnered with leading universities, and trained models on millions of expert-tagged images. Now, they’re scaling globally — and need a world-class Lead Data Scientist to help push the boundaries of computer vision, video analysis, and multimodal LLMs while solving real-world challenges.


Role Overview

They are looking for an experienced Lead Data Scientist to spearhead machine-learning initiatives, with particular focus on computer vision, large language models, and production ready ML pipelines in Azure. You will act as the technical lead for the team, setting direction, guiding best practices, and ensuring the successful delivery of high-impact AI solutions.


Key Responsibilities

  • Develop, train, and deploy computer vision models (object detection, image classification, segmentation, multi-modal learning)
  • Fine-tune, evaluate, and productionise multi-modal LLMs for business applications.
  • Drive experimentation and prototyping of advanced ML / AI techniques
  • Provide technical direction, mentoring, and hands‑on guidance to the data science team.
  • Work with engineering, product, and business stakeholders to align ML strategy with business goals.
  • Architect and productionise end-to-end ML pip...


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Scientist - Agentic AI - Macquarie Group

Lead Data Scientist: AI for Fraud & Identity

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.