Cloud DevOps Ltd
Machine Learning Engineer
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Company Description
Cloud DevOps Ltd is a technology company focused on delivering scalable, cloud-based solutions for modern enterprises. The organization specializes in integrating advanced automation and data-driven systems to improve reliability, performance, and deployment workflows. Teams at Cloud DevOps Ltd collaborate across engineering and operations to build secure, resilient platforms that support business growth. The company values innovation, continuous learning, and practical problem-solving in a fast-paced environment.
Role Description
The Machine Learning Engineer will design, develop, and deploy machine learning models that support core products and internal tools at Cloud DevOps Ltd. Day-to-day responsibilities include:
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- Building data pipelines
- Training and evaluating models
- Optimizing algorithms for performance
- Collaborating with software engineers and data professionals to integrate ML solutions into production systems
The engineer will participate in code reviews, document technical solutions, and use best practices for testing and monitoring deployed models. This is a full-time, on-site role based in Cardiff.
Qualifications
- Strong foundation in Machine Learning and Deep Learning Frameworks
- Skills in Statistics and Pattern Recognition for data modeling and analysis
- Experience with Neural Networks and modern machine learning frameworks
- Proficiency in at least one programming language commonly used in ML (e.g., Python, Go) and familiarity with version control tools
- Ability to work collaboratively in cross-functional teams and communicate complex technical concepts clearly
- A bachelor’s or master’s degree in Computer Science, Data Science, Engineering, or a related field is preferred
- Experience with cloud platforms, MLOps practices, and deploying models to production environments is beneficial
- Familiar with Langhain, Langgraph, Choreography and Agentic AI
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Added Advantage
- Certifications across AWS or Azure would be great but not essential
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