Machine Learning Engineer I

Location Conshohocken, PA office. What you’ll be doing Develop, train, and evaluate ML models using Python (scikit-learn, PyTorch/TensorFlow) Implement feature engineering pipelines for structured insurance datasets Perform model validation, hyperparameter tuning, and performance optimization Apply statistical techniques and experimentation methodologies Build and manage ML workflows using Azure Machine Learning (Azure ML) Work with Azure Data Lake Storage and Azure Blob Storage for large‑scale data processing Develop data pipelines using Azure Data Factory or Azure Synapse Utilize Databricks (PySpark) for distributed data processing (preferred) Deploy models using Azure ML endpoints or containerized services Support CI/CD pipelines for ML workflows (Azure DevOps or GitHub Actions) Monitor models for performance, drift, and reliability in production Maintain model versioning, experiment tracking, and reproducibility (e.g., MLflow) Write production‑quality Python code with modular design and testing Use Git for version control and collaborate via code reviews Package ML models and pipelines for scalability and reuse Preferred Qualifications Experience with Azure Machine Learning pipelines and model deployment Familiarity with Databricks / PySpark Exposure to Docker and containerization Understanding of REST APIs and model serving Experience with MLflow or similar experiment tracking tools Knowledge of insurance datasets or financial services domain Exposure to NLP or document AI (useful for claims and underwriting) Key Competencies Strong Python engineering mindset (not just notebooks) Cloud‑first thinking (Azure‑native solutions) Focus on scalability, reliability, and maintainability Curiosity and willingness to learn new tools quickly Benefits Summary Competitive base salary and incentive awards tied to company and individual performance. Retirement savings plan with employer contributions.

Health and dental coverage including PPO and HDHP. Paid time off, parental leave, and adoption assistance. Professional development and tuition reimbursement.

Equal opportunity employer. #J-18808-Ljbffr