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MLOps Engineer

krtrimaIQ Cognitive Solutions

5 years

0 Lacs

India

Posted:20 hours ago| Platform:

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Skills Required

aws sagemaker mlflow learning management ml flexibility ai design automate model training testing tracking versioning deployment devops monitoring optimization data research compliance software development engineering programming python scala spark docker kubernetes airflow terraform orchestration experimentation collaborative

Work Mode

Remote

Job Type

Full Time

Job Description

Job Title: MLOps Engineer – AWS SageMaker & MLflow (Remote)

Location: Fully Remote (India Preferred)

Experience Level: 5+ Years

Employment Type: Full-Time

Company: KrtrimaIQ Cognitive Solutions

Job Summary:

KrtrimaIQ Cognitive Solutions is looking for a Senior MLOps Engineer with deep expertise in AWS SageMaker, MLflow, and end-to-end machine learning lifecycle management. The ideal candidate will have hands-on experience in deploying and managing scalable ML solutions in production environments and a passion for building reliable MLOps systems.

This is a fully remote opportunity offering flexibility and the chance to work on innovative AI/ML products for global enterprises.

Key Responsibilities:

Design, build, and maintain scalable and secure MLOps pipelines using AWS SageMaker and MLflow
Automate ML model lifecycle: training, testing, tracking, versioning, and deployment to production
Implement CI/CD pipelines and DevOps practices for ML infrastructure
Ensure reproducibility, monitoring, and performance optimization of deployed models
Collaborate closely with Data Scientists, Data Engineers, and DevOps teams to streamline workflows
Contribute to MLOps research and explore new tools and frameworks in the production ML space
Ensure compliance with best practices in cloud computing, software development, and data security

Must-Have Qualifications:

5+ years of professional experience in Software Engineering or MLOps
Expertise in AWS, specifically AWS SageMaker for building and deploying ML models
Hands-on experience with MLflow for model tracking, versioning, and deployment
Strong programming skills in Python (R, Scala, or Spark is a plus)
Solid experience in production-grade development and infrastructure automation
Strong problem-solving, analytical, and research skills

Preferred Qualifications:

Experience with AWS DataZone
Familiarity with Docker, Kubernetes, Airflow, Terraform, or other orchestration tools
Understanding of data versioning, feature stores, and ML monitoring tools
Exposure to MLOps research and experimentation in startup/innovation environments

What We Offer:

💻 100% Remote Work Flexibility
🌐 Exposure to enterprise-grade AI and MLOps use cases
🤝 Collaborative work culture focused on innovation and learning
🚀 Fast-paced startup-like environment with global project opportunities

#mlops #awssagemaker #mlflow #python #aws #docker #immediatejoiner #remotemode #ai/mlsolutions

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MLOps Engineer