TechniPros
AI ML Engineer - Malvern, PA
Malvern, Pennsylvania, USA · Contract
Sponsorship not specifiedDetected 35 days ago
AWSCI/CDDevOpsMachine LearningMLOpsCommunicationCollaborationProblem SolvingAdaptability
About the role
- 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.
Responsibilities
- Build and manage end-to-end ML pipelines using AWS cloud services.
- Implement and manage ML model lifecycle processes from development through production.
- Build scalable ML workflows using AWS SageMaker, S3, Lambda, Step Functions, and API Gateway.
- Implement CI/CD pipelines using AWS CodePipeline and CodeBuild.
- Collaborate with data scientists, engineers, and business teams to deliver ML solutions.
Nice to have
- 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.
Skills
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to work with cross-functional technical teams.
- Strong ownership and attention to detail.
- Ability to troubleshoot complex technical issues.
- Adaptability to evolving technologies and business requirements.
- Machine Learning, MLOps, AWS, SageMaker, S3, Lambda, Step Functions, API Gateway, CodePipeline, CodeBuild, CI/CD, DevOps,
- Feature Engineering, ML Model Deployment, Model Lifecycle Management Best Regards:
Benefits
- Design, develop, deploy, and maintain scalable machine learning solutions.
- Develop, deploy, and monitor machine learning models in production environments.
- Perform feature engineering and optimize machine learning models for production use.
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