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

Apply Now

Lead Machine Learning Engineer

Glasgow
7 months ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Are you a seasoned Machine Learning Engineer ready to take the next step in your career by productionising GenAI and Recommender Systems at huge scale?

Do you have a passion for machine learning and a keen interest in the transformative potential of generative AI?

About the Role:

You'll join a global online marketplace as a Lead Machine Learning Engineer in an ML Enablement team. In this role, you'll be at the forefront of productionising GenAI and Recommender Systems at scale.

Your expertise will drive significant change and help shape the future of the their business and how hundreds of millions of customers interact with their platform.

Key Responsibilities

Productionise GenAI and Recommender Systems: Develop and implement scalable solutions for a global platform.

MLOps Focus: Utilise MLflow, SageMaker, and machine learning libraries to streamline and optimise ML operations.

Collaborate and Innovate: Work with a team of brilliant minds on projects that directly impact hundreds of millions of users worldwide.

Technical Requirements

Machine Learning Expertise: Previous experience as a Senior Data Scientist or ML Engineer, with hands-on experience deploying ML models in production within a commercial environment. Strong understanding of ML models and their applications.

Programming and Frameworks: Proficiency in Python and SQL,. Hands-on experience with ML frameworks like TensorFlow, PyTorch, and Scikit-Learn.

Cloud and Containerisation: Experience with cloud platforms (AWS, GCP, or Azure) and containerisation technologies (Docker, Kubernetes).

MLOps and Responsible AI: Familiarity with CI/CD pipelines, model registries, ML observability tools, responsible AI principles, model monitoring, and data privacy best practices.

Compensation: Base salary of £90-95k, plus bonuses and a host of other benefits including ability to travel internationally to global offices, or work from anywhere globally for 1 month per year.

Location: London, Hybrid. 2 days on-site per week.

Apply now for immediate consideration

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 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.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.