Senior ML Engineer
Core
Design, build, and scale machine learning systems for advanced analytics, predictive modeling, and data-driven decision-making, embedding models into enterprise applications.
Role type
Senior ML Engineer (MLOps & Productionization)
Builds
Production ML pipelines, models, and workflows for enterprise applications
Domain
Enterprise analytics, predictive modeling, cloud-native data engineering
Deliverable
production ML models
Required skills
End-to-end ML pipeline development, model training and inference at scale, feature engineering, model monitoring and retraining, MLOps practices, cloud platform expertise (AWS/Azure), distributed data processing
Preferred skills
Cloud certifications (AWS/Azure), data engineering/ML engineering certifications
Technologies
AWS SageMaker, Azure Machine Learning, Databricks, Spark, Delta Lake, Azure DevOps, GitHub
Responsibilities
Develop and maintain end-to-end ML pipelines; Collaborate with data scientists to operationalize models; Monitor model performance and implement continuous improvement processes
Seniority
Senior, hands-on IC
