ML Engineer - Malvern, PA
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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:
Email: peerbhi
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:
Email: peerbhi