About the Company

Stellar IT Solutions LLC provides technology solutions and engineering support for enterprise initiatives. The company is hiring a Machine Learning Engineer to support Cisco Learning's opportunity-assessment solution, with a focus on building reliable machine learning pipelines and integrating models into operational systems.

About the Role

Stellar IT Solutions LLC is seeking a Machine Learning Engineer to turn machine learning and analytical strategies into reusable feature-engineering pipelines, end-to-end ML workflows, and production-ready solutions. This role focuses on the full model lifecycle, including data preprocessing, training, evaluation, inference, monitoring, and operational integration. The selected candidate will work with structured and unstructured data, develop reproducible ML workflows, and support model versioning, experiment tracking, automated testing, and retraining. The role also involves integrating machine learning components with enterprise data environments and downstream systems through APIs and other integrations.

Key Responsibilities

Translate machine learning and analytical strategies into reusable feature-engineering pipelines and end-to-end ML workflows. Develop and maintain production-oriented machine learning solutions, including data preprocessing and transformation. Build and manage ML pipelines covering model training, evaluation, inference, and operational handoff. Support model registries, model versioning, and experiment tracking. Implement model monitoring and automated testing practices suitable for production environments. Develop retraining workflows to maintain model performance over time. Build reproducible pipelines for data ingestion, data access, and integration with enterprise data environments. Process structured and unstructured data for machine learning applications. Integrate ML components into operational systems through APIs and downstream integrations. Work within cloud-based machine learning and data environments to support end-to-end production delivery. Apply sound software development and version-control practices to maintain reliable, maintainable solutions.

Required Qualifications

Strong programming skills in Python and SQL. Experience with Pandas, NumPy, or comparable data-processing libraries. Ability to work with both structured and unstructured data. Hands-on experience with feature engineering and ML pipeline development. Experience with model training, evaluation, and inference. Knowledge of data preprocessing and transformation techniques. Experience with Scikit-learn or comparable machine learning frameworks. Understanding of production-oriented ML development and model operationalization. Experience with model registries, model versioning, and experiment tracking. Knowledge of model monitoring, automated testing, and retraining workflows. Experience developing reproducible ML pipelines and data ingestion or access pipelines. Familiarity with cloud-based ML and data environments. Experience integrating APIs, downstream systems, and enterprise data platforms. Strong software development and version-control practices.

Preferred Qualifications

Experience with MLflow or comparable machine learning lifecycle tools. Familiarity with feature stores. Experience with containerization technologies. Experience using cloud-based machine learning platforms. Experience developing APIs and system integrations. Knowledge of NLP and text-processing pipelines. Experience with document ingestion and vector-based data workflows. Experience with model inference optimization and monitoring. Experience implementing automated ML testing and retraining. Background working with enterprise data platforms. Previous experience with Cisco, supported by relevant machine learning engineering skills. Technical Skills Python, SQL, Pandas, NumPy, Scikit-learn, and MLflow. Primary Focus Machine learning engineering, feature pipelines, model operationalization, MLOps, and data/ML integration. Work Arrangement Remote position. Location: St. Louis, Missouri.

Compensation

Hourly rate: $60–$65 USD.