ML Engineer

Job Title: ML Engineer
Location: Malvern PA
Can do Only W2 No C2C

Job Summary:

We are seeking an experienced Machine Learning Engineer with strong MLOps expertise on AWS to design build deploy and maintain scalable machine learning solutions. The ideal candidate will have hands-on experience with AWS ML services productionizing machine learning models automated CI/CD pipelines and end-to-end model lifecycle management.
The candidate should have strong knowledge of Machine Learning DevOps AWS cloud services feature engineering and production ML systems with a focus on reliability performance and cost optimization.

Key Responsibilities:

• Design develop deploy and maintain scalable machine learning solutions.
• Build and manage end-to-end ML pipelines using AWS cloud services.
• Implement and manage ML model lifecycle processes from development through production.
• Develop deploy and monitor machine learning models in production environments.
• Build scalable ML workflows using AWS SageMaker S3 Lambda Step Functions and API Gateway.
• Perform feature engineering and optimize machine learning models for production use.
• Implement CI/CD pipelines using AWS CodePipeline and CodeBuild.
• Improve system reliability performance scalability and cost efficiency.
• Monitor ML applications and troubleshoot production issues.
• Collaborate with data scientists engineers and business teams to deliver ML solutions.

Required Skills:

• Machine Learning
• MLOps
• AWS Cloud Services
• AWS SageMaker
• Amazon S3
• AWS Lambda
• AWS Step Functions
• AWS API Gateway
• CI/CD Implementation
• AWS CodePipeline
• AWS CodeBuild
• Feature Engineering
• Machine Learning Model Deployment
• Model Monitoring
• End-to-End ML Lifecycle Management
• Productionizing ML Models
• DevOps Practices
• Cloud-based ML Architecture

Preferred Qualifications:

• 8-10 years of experience in Machine Learning Engineering MLOps or related fields.
• Experience building enterprise-scale machine learning platforms.
• Strong experience with AWS-based ML solutions.
• Experience implementing automation and deployment frameworks.
• Experience optimizing ML workloads for performance and cost.
• Experience working with production-grade ML systems.

Best Regards:

Peerbhi SK
Phone: 1-
Email: peerbhi@