Senior AWS MLOps Engineer
Senior AWS MLOps Engineer
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Job Description
We are seeking a highly skilled AWS MLOps Engineer with a minimum of 5 years of DevOps experience particularly in managing ML pipelines in AWS. The ideal candidate has successfully built and deployed at least two MLOps projects using Amazon SageMaker or similar services with a strong foundation in infrastructure as code and a keen understanding of MLOps best practices.
Key Responsibilities:
Maintain and enhance existing ML pipelines in AWS with a focus on Infrastructure as Code using CloudFormation.
Implement minimal but essential pipeline extensions to support ongoing data science workstreams.
Document infrastructure usage architecture and design using tools like Confluence GitHub Wikis and system diagrams.
Act as the internal infrastructure expert collaborating with data scientists to guide and support model deployments.
Research and implement optimization strategies for ML workflows and infrastructure.
Work independently and collaboratively with cross-functional teams to support ML product deployment and re-platforming initiatives.
Qualifications :
5 years of hands-on DevOps experience with AWS Cloud.
Proven experience with at least two MLOps projects deployed using SageMaker or similar AWS services.
Strong proficiency in AWS services: SageMaker ECR S3 Lambda Step Functions.
Expertise in Infrastructure as Code using CloudFormation for dev/test/prod environments.
Solid understanding of MLOps best practices and Data Science principles.
Proficient in Python for scripting and automation.
Experience building and managing Docker images.
Hands-on experience with Git-based version control systems such as AWS CodeCommit or GitHub including GitHub Actions for CI/CD pipelines.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
