Request ID:101260-1
Title: AWS ML Engineer
Location: Malvern PA
Duration: 6+ Months
Salary Range: $52- $57 an hour on W2
Job Description:
Design, build, and deploy scalable Machine Learning solutions on AWS using SageMaker, ensuring high performance, reliability, and security.
Develop and maintain end-to-end ML pipelines, including data preparation, model training, hyperparameter tuning, deployment, and monitoring.
Collaborate with data scientists, engineers, and business stakeholders to operationalize ML models, automate workflows, and drive business outcomes through AI/ML solutions.
Detailed Technical skills -
Amazon SageMaker Expertise Strong experience with SageMaker Studio, Training Jobs, Pipelines, Model Registry, Feature Store, and Endpoint Deployment.
Machine Learning & Deep Learning Hands-on experience building, training, tuning, and deploying ML/DL models using Scikit-learn, XGBoost, TensorFlow, and PyTorch.
AWS Cloud Services Proficiency in S3, EC2, IAM, Lambda, ECR, ECS/EKS, CloudWatch, and Step Functions for ML workloads.
MLOps & CI/CD Experience implementing automated ML pipelines, model versioning, deployment automation, monitoring, and retraining workflows.
Python Programming Strong coding skills with Python and ML libraries such as Pandas, NumPy, Scikit-learn, and Boto3.
Data Engineering & Analytics Experience with data ingestion, transformation, and processing using AWS Glue, Athena, Redshift, and EMR.
Model Monitoring & Governance Expertise in data drift detection, model performance monitoring, explainability, and governance using SageMaker monitoring capabilities.
Solution Architecture & Leadership Ability to design scalable end-to-end ML solutions on AWS, lead technical discussions, mentor teams, and collaborate with business stakeholders.
Skills: Digital : Python~Digital : Machine Learning
Experience Required: 6-8
Appreciate your quick response and please feel free to reach me out for any query you may have.
Thanks