Role: MLOps Implementation Engineer
Location: Reston,VA(Onsite)
Job Description
As an MLOps Implementation Engineer, your primary responsibility will be to understand and implement our pre-developed MLOps strategies across various tools, including Domino Data Lab and AWS SageMaker. You will play a crucial role in containerizing these models and developing automated processes to deploy them into AWS Batch, Amazon Elastic Container Registry (ECR), or Amazon Elastic Kubernetes Service (EKS).
Additional info :
Key Responsibilities:
- Interact with Analytics teams to gather requirements for Python and R container images.
- Resolve dependencies for the required Python and R packages.
- Identify and address any security vulnerabilities in the container images.
- Develop and maintain custom container images to ensure compatibility with SageMaker and Domino Data Lab.
- Test and validate container images to ensure they meet performance and reliability standards.
- Collaborate with cross-functional teams to ensure seamless integration and deployment of custom images.
- Document processes and provide training as needed to ensure team members can effectively use and manage the custom containers.
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Proven experience in managing and developing custom containers, especially with Python and R.
- Strong expertise with Amazon SageMaker and its various components.
- Experience with containerization technologies such as Docker.
- Knowledge of dependency management and package resolution for Python and R.
- Understanding of security best practices and vulnerability mitigation for container images.
- Familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI/CD).
- Strong programming skills in Python and/or R.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
Preferred Qualifications:
- Experience with AWS Cloud and its services like S3, ECR, EKS etc.
· Knowledge of infrastructure as code (IaC) using tools like Terraform or AWS CloudFormation.
· Understanding of machine learning model lifecycle management.
| Bharath Pammi Team Lead |  | |
| https://www.linkedin.com/in/pammi-sai-bharath-340331113/ | ||
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