Machine Learning Engineer

Remote Machine Learning Engineer role focused on turning ML and analytics strategies into production-ready feature pipelines, workflow automation, and integrated model operations for Cisco Learning’s opportunity-assessment solution.

Responsibilities

• Translate ML and analytical strategies into repeatable feature-engineering pipelines, ML workflows, model lifecycle processes, and operational integrations.
• Build and maintain feature engineering workflows.
• Develop ML pipeline capabilities, including data preprocessing/transformation and training preparation.
• Own model training and evaluation tasks across the lifecycle.
• Support model inference needs for downstream usage.
• Design data preprocessing/transformation steps for structured and unstructured inputs.
• Deliver production-oriented ML development components.
• Implement model registries and model versioning.
• Enable experiment tracking and lifecycle visibility.
• Set up model monitoring practices for operational performance.
• Develop automated testing to validate pipelines and ML components.
• Create and maintain retraining workflows that support repeatable execution.
• Ensure reproducible ML pipelines from ingestion to inference.
• Build data ingestion/access pipelines and support enterprise data environments.
• Integrate with cloud-based ML/data environments.
• Develop APIs and/or downstream integrations that connect models to operational systems.

Requirements

• Strong Python
• SQL
• Pandas / NumPy or comparable data-processing libraries
• Experience with structured and unstructured data processing
• Solid software-development and version-control practices
• Hands-on feature engineering and ML pipeline development
• Experience with model training and evaluation
• Model inference experience
• Data preprocessing/transformation experience
• Scikit-learn or comparable ML frameworks
• Production-oriented ML development experience
• Working knowledge of model registries and model versioning
• Experiment tracking experience
• Model monitoring experience
• Automated testing and retraining workflows
• Ability to deliver reproducible ML pipelines
• Experience with data ingestion/access pipelines
• Familiarity with cloud-based ML/data environments
• Experience developing APIs and/or downstream integrations
• Experience working within an enterprise data environment

Technologies

• Python
• SQL
• Pandas
• NumPy
• Scikit-learn
• MLflow

Primary Focus

• ML Engineering
• Feature Pipelines
• Model Operationalization
• MLOps
• Data/ML Integration

Preferred Skills

• MLflow or comparable ML lifecycle tooling
• Feature Store experience
• Containerization
• Cloud ML platforms
• API/integration development
• NLP/text-processing pipelines
• Document/vector ingestion
• Model inference and monitoring
• Automated ML testing/retraining
• Enterprise data-platform experience
• Production-oriented ML solutions
• Previous Cisco experience with the appropriate ML engineering skill set

Location: St. Louis, MO (remote)

Compensation: USD 60 - 65 per hourly