ML Pipeline Architect

1 day ago

Jaipur, Rajasthan, India beBeeMachineLearning Full time ₹ 20,00,000 - ₹ 25,00,000

Job Title : MLOps Engineer

">Overview

As a seasoned software engineer with 5+ years of experience, we are looking for a highly skilled and driven professional to join our team as an MLOps Engineer. This role demands expertise in deploying machine learning models into production and managing the complete ML lifecycle using AWS services.

">Key Responsibilities

- Design, develop, and maintain scalable MLOps pipelines for deploying and managing machine learning models in production.
- Implement core MLOps concepts such as model training, feature engineering, model registration, endpoint deployment, batch inference, model monitoring, and data drift detection.
- Build secure ML pipelines using AWS SageMaker, Lambda, API Gateway, and other AWS services.
- Use Docker and YAML to containerize and configure the ML workflows.
- Set up and manage CI/CD pipelines using GitLab, incorporating best practices such as artifact scanning, vulnerability checks, automated testing, and deployment.
- Develop infrastructure using AWS CDK to provision and manage AWS resources programmatically.
- Collaborate with Data Scientists, DevOps, and Engineering teams to ensure seamless integration of models into production environments.

">Required Skills and Qualifications

- Minimum 5 years of experience in Software Engineering and MLOps.
- Hands-on development experience with AWS, especially SageMaker.
- Practical knowledge of MLflow, GitLab, and AWS CDK.
- Familiarity with AWS Lambda, Docker, API Gateway, and YAML scripting.
- Proficiency in one or more programming languages: Python, R, Scala, or Spark.
- Strong understanding of production-grade ML systems including security, scalability, and monitoring.
- Good exposure to CI/CD best practices using GitLab CI Pipelines.
- Understanding of artifact scanning and vulnerability assessment in CI/CD environments.

">Benefits

- Opportunity to work on cutting-edge MLOps projects and contribute to research and innovation.
- Collaborative and dynamic team environment.

">Other Information

- Exposure to AWS DataZone is a plus.

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