The Role
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As a Machine Learning Engineer, you will be in charge of model development to deployment and production monitoring. You will be challenged with real-world, large-scale challenges whilst applying solid engineering principles to build robust, scalable, and reliable machine learning systems.
Key Responsibilities
Design, build, and deploy machine learning models for production use cases such as recommendation systems, NLP, computer vision, and predictive analytics
Develop and maintain scalable pipelines for training, evaluation, and inference
Work with both structured and unstructured data across a variety of domains
Implement efficient data preprocessing, feature engineering, and transformation workflows
Ensure data quality, integrity, and compliance with governance standards (e.g., GDPR)
Optimize models for performance, scalability, and cost-efficiency in production
Collaborate closely with data engineers, software engineers, and product stakeholders
Deploy and manage models using cloud platforms (AWS, Azure, or GCP) and containerization tools
Build monitoring, validation, and testing frameworks to ensure model reliability
Continuously improve model performance through experimentation and iteration
Contribute to MLOps practices, including CI/CD, model versioning, and reproducibility
Your Profile
3–5+ years of experience in Machine Learning Engineering, AI Engineering, or a related field
Strong programming skills in Python
Hands-on experience with ML/DL frameworks such as TensorFlow or PyTorch
Solid understanding of machine learning algorithms, evaluation methods, and optimization techniques
Proven experience building and deploying ML pipelines in production environments
Familiarity with data engineering concepts (ETL/ELT, data pipelines)
Experience with cloud platforms (AWS, Azure, xphnsxz or GCP)
Experience with containerization tools (Docker, Kubernetes)
Understanding of MLOps tools and practices (e.g., MLflow, Airflow)
Experience working with large-scale or complex datasets
Awareness of data privacy and governance best practices
What’s Offered
Competitive salary and comprehensive benefits package
Hybrid working environment
Opportunity to work on impactful, scalable ML systems in a modern tech setting
Clear path for professional growth and development
Apply
If this opportunity interests you, apply now or send your CV along with a short cover letter to
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