Lead Machine Learning Engineer

Glasgow
1 month ago
Applications closed

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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

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