Intermediate Machine Learning Engineer
Core
Designing and implementing ML pipelines and services in cloud and on-premise environments to support the operationalization of ML models across the organization.
Role type
Intermediate Machine Learning Engineer (MLOps)
Builds
Scalable ML solutions and operationalized ML models
Domain
Insurance / Cloud Infrastructure / Data Engineering
Deliverable
production ML models
Required skills
Python, SQL, Pandas, NumPy, scikit-learn, XGBoost, AWS, Snowflake, Linux, Jenkins, Docker, CI/CD, model versioning, retraining workflows
Preferred skills
Apache Spark, Snowpark, Azure, GCP, MLflow, Airflow
Responsibilities
Design and implement ML pipelines and services; Collaborate with cross-functional teams to gather requirements; Support model deployment, monitoring, and performance optimization; Apply MLOps practices; Work with Snowflake and AWS services; Ensure adherence to data privacy, security, and compliance standards; Participate in code reviews and knowledge sharing
Seniority
Intermediate, hands-on IC
