MLOps Engineer(NJ)
Core
Building, deploying, testing, and monitoring machine learning models and pipelines for Fortune 500 clients using cloud infrastructure.
Role type
MLOps Engineer
Builds
Production ML pipelines, training workflows, and monitoring solutions for client analytics projects
Domain
Advanced analytics consulting, Cloud Infrastructure (AWS)
Deliverable
production ML models
Required skills
AWS SageMaker, Apache Airflow, Python, Docker, Pytest, Great Expectations, Terraform, CloudFormation, ML frameworks (Scikit-learn, TensorFlow, Keras), Spark, Hadoop, FastAPI, Flask, Kubernetes, MLflow
Preferred skills
Experience with Oracle, Athena, Service Catalog, SNS, SES
Technologies
AWS SageMaker, AWS CFT, AWS CodePipeline, Lambda, Airflow, Pytest, Great Expectations, Terraform, Apache Airflow, Astronomer, Docker, Scikit-learn, TensorFlow, Keras, Pandas, Numpy, Scipy, Spark, Hadoop, FastAPI, Flask, ReST, MLflow, Kubernetes, Oracle, Athena
Responsibilities
Develop Airflow DAGs for training and scoring pipelines; Implement monitoring solutions using Lambda and Dash; Develop data quality solutions leveraging Great Expectations; Build testing frameworks with Pytest; Manage ML model lifecycle including training, deployment, and evaluation on AWS SageMaker
Seniority
Mid-Senior, hands-on IC
