Lead Machine Learning Engineer

Glasgow
1 week ago
Create job alert

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

Related Jobs

View all jobs

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning Engineer - GenAI

Lead Machine Learning Engineer

Lead Machine Learning Engineer

Lead Machine Learning 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.