Machine Learning Engineer

About The Role

Join Data Eminence as a remote Machine Learning Engineer to build intelligent, data-driven solutions that automate processes, uncover patterns, and drive business decisions. You will lead the full machine learning lifecycle: from collecting and cleaning structured/unstructured datasets to deploying optimized models into production environments.

Your Responsibilities

• Data Engineering:

• Collect, clean, preprocess, analyze, transform, and engineer features for both structured and unstructured data using Python (NumPy, Pandas).

• Model Development:

• Implement models for classification, regression, clustering, and prediction; experiment with algorithms and hyperparameters.

• Evaluation & Optimization:

• Train/validate models using appropriate metrics (accuracy, precision, recall) to identify improvement opportunities.

• Pipeline Construction:

• Develop reusable workflows and integrate trained models into backend applications via REST APIs.

• Docker & Deployment:

• Assist in deploying solutions to cloud platforms (AWS, Azure, GCP) or on-premise environments; monitor performance post-launch.

Tech Stack

We provide hands-on experience with Python, Scikit-learn, TensorFlow/PyTorch, SQL, Jupyter Notebook, and Git/GitHub. Familiarity with cloud services (Docker) is a plus.