Senior MLOps Engineer – AWS

Amtex Systems Inc is an information technology and talent solutions company offering talent and BI consulting to the companies in US for over 25 years.

Our solutions are designed to fill resource gaps, by providing the right candidates who deliver value to the organization. Our propensity to nurture and build strong relationships with our clients helps us better understand their business demands and gives us the ability to provide services that are on time and rise above the rest.

Title: Senior MLOps Engineer – AWS

Location: Remote

Duration: Fulltime

Job Description:

• Design, build, and deploy machine learning models into production AWS environments, primarily leveraging Amazon SageMaker or comparable AWS hosting solutions.
• Package and operationalize trained models developed in Databricks or other ML development environments.
• Build and integrate model-serving solutions using AWS Lambda, API Gateway, and other AWS services.
• Develop and maintain infrastructure as code using Terraform to provision and manage cloud resources.
• Design and implement CI/CD pipelines to automate model deployment, testing, versioning, and releases.
• Implement production monitoring, logging, and alerting using Amazon CloudWatch.
• Troubleshoot production issues related to model performance, application integration, infrastructure, and service availability.
• Partner with cloud infrastructure, networking, and security teams to ensure compliance with enterprise standards.
• Support real-time and batch inference solutions, including potential migration from batch processing to real-time serving.
• Establish reusable deployment frameworks, documentation, and operational runbooks.
• Mentor and collaborate with internal engineers to transfer knowledge and establish sustainable MLOps practices.

Required Qualifications

• Proven hands-on experience personally deploying and supporting machine learning models in production AWS environments.
• Strong experience with AWS services, particularly SageMaker, Lambda, API Gateway, and CloudWatch.
• Hands-on Terraform experience provisioning and managing AWS infrastructure.
• Experience building or maintaining CI/CD pipelines for machine learning or cloud application deployments.
• Understanding of model packaging, hosting, inference endpoints, and application integration.
• Experience troubleshooting production systems and supporting deployed ML applications.
• Knowledge of AWS networking, IAM, VPC configurations, and enterprise security requirements.
• Strong software engineering fundamentals and experience collaborating with cloud and platform engineering teams.
• Ability to communicate technical concepts, explain architectural decisions, and document solutions.
• Experience working within large enterprise environments with established security and infrastructure controls.