The Machine Learning Engineer focuses on building predictive models and deploying them into production environments. This role requires strong experience with Python and machine learning libraries such as Scikit-learn, NumPy, and Pandas. Understanding supervised and unsupervised learning techniques is essential.
The engineer will work closely with data scientists to transform experimental models into scalable services. Responsibilities include data preprocessing, feature engineering, model training, evaluation, and monitoring. Experience with handling large datasets and optimizing algorithms for performance is required.
The role also involves integrating machine learning models with APIs and backend systems. Familiarity with model versioning, automation, and MLOps concepts is a plus. This position is ideal for engineers who enjoy applied machine learning and production-ready solutions.