Machine Learning Engineer

Hands-on engineering resource responsible for converting ML and analytical strategies into repeatable feature-engineering pipelines, ML workflows, model lifecycle processes, and operational integrations in support of Cisco Learning s opportunity-assessment solution.

Languages & Data

• Strong Python

• SQL
• Pandas / NumPy or comparable data-processing libraries
• Structured and unstructured data processing
• Software-development and version-control practices

ML Engineering

Feature engineering

• ML pipeline development
• Model training and evaluation
• Model inference
• Data preprocessing/transformation
• Scikit-learn or comparable ML frameworks

Production-oriented ML development

MLOps / Model Lifecycle

Model registries

• Model versioning
• Experiment tracking
• Model monitoring
• Automated testing
• Retraining workflows

Reproducible ML pipelines

Data / Integration

Data ingestion/access pipelines

• Cloud-based ML/data environments
• APIs and/or downstream integrations

Enterprise data environment

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