You will work across machine learning, data engineering, and software development to build scalable, production-ready AI systems.
Design, develop, and implement machine learning and AI models for various business needs.
Build and maintain data pipelines and training workflows.
Evaluate model performance and run experiments to improve accuracy, efficiency, and reliability.
Deploy models into production using MLOps best practices (CI/CD, model versioning, monitoring).
Collaborate with data scientists, software engineers, and product teams to deliver AI-driven features.
Strong experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
Proficiency in Python and experience building production-grade ML code.
Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes).
Knowledge of data engineering practices, including data pipelines and ETL.
