onsite
Machine Learning Engineer - Vermelo RPO
ML Engineer
Lead the design and deployment of automated ML pipelines for insurance risk modelling, leveraging Python, AWS, and data engineering best practices to deliver scalable, high‑performance solutions.
About the role
Key Responsibilities
- Design, develop, and maintain end‑to‑end machine learning pipelines for insurance risk and pricing models.
- Collaborate with data scientists and domain experts to translate business requirements into robust ML solutions.
- Implement scalable data ingestion, feature engineering, and model training workflows on AWS.
- Ensure model quality, reproducibility, and compliance with regulatory standards.
- Monitor model performance in production and iterate for continuous improvement.
Requirements
- Strong experience in Python and ML libraries (scikit‑learn, TensorFlow, PyTorch).
- Proficiency with AWS services (SageMaker, Lambda, S3, Glue) and containerization (Docker).
- Solid background in data engineering, SQL, and ETL processes.
- Excellent problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
Skills
pythonmachine learningawssql