AWS MLOps Engineer

6 days ago

Dombivli, India Tata Consultancy Services Full time

Role -AWS MLOps (Machine Learning Operations) Engineer

Exp-4 to 8 years

Loaction-Bangalore/Kolkata




AWS MLOps (Machine Learning Operations) Engineer with 5-6 years relevant experience in AWS personalization(Personalize is an ML service that helps developers quickly build and deploy a custom recommendation engine with real-time personalization and user) - is responsible for designing, implementing, and managing machine learning infrastructure and workflows on the AWS platform. Here's a basic breakdown of job design for an AWS MLOps Engineer:


1. **Infrastructure Setup:** Designing and deploying AWS infrastructure components such as EC2 instances, S3 buckets, VPCs, and networking configurations tailored for machine learning workloads.


2. **Automated Model Deployment:** Developing automated pipelines for model training, evaluation, and deployment using AWS services like SageMaker, AWS Lambda, and AWS Batch.


3. **Monitoring and Optimization:** Implementing monitoring solutions to track model performance, resource utilization, and overall system health. Employing AWS CloudWatch, AWS X-Ray, or custom monitoring tools.


4. **Security and Compliance:** Ensuring the security of data and models by implementing encryption, access controls, and compliance measures following AWS best practices and industry standards.


5. **Collaboration and Documentation:** Collaborating with data scientists, engineers, and stakeholders to streamline workflows, document processes, and share best practices.


6. **Cost Optimization:** Optimizing costs by utilizing AWS cost management tools and strategies, such as selecting the right instance types and scaling resources efficiently.


7. **Continuous Integration/Continuous Deployment (CI/CD):** Establishing CI/CD pipelines through Terraform for ML models to enable automated testing, validation, and deployment.


8. **Troubleshooting and Support:** Diagnosing and resolving issues related to infrastructure, deployment, or performance to ensure smooth operations.


9. **Adopting New Technologies:** Staying updated with the latest AWS services and machine learning frameworks to propose and implement improvements in the existing infrastructure and processes.


10. **Documentation and Training:** Documenting processes, best practices, and creating training materials to facilitate knowledge transfer and assist team members.


This role requires a deep understanding of AWS services, machine learning concepts, programming skills, and DevOps practices to effectively manage and optimize the machine learning lifecycle on the AWS cloud.


Talent Acquisition Team

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