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ML Ops Engineer

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NStarX

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Location:
India , Hyderabad

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

As an MLOps Engineer, you will be responsible for building, maintaining, and optimizing machine learning (ML) operations infrastructure to enable smooth deployment and scaling of ML models. You will collaborate with data scientists, software engineers, and IT teams to streamline model workflows, enhance automation, and ensure high availability of ML solutions.

Job Responsibility:

  • Develop and manage infrastructure for end-to-end ML workflows including model training, deployment, monitoring, and maintenance
  • Implement CI/CD pipelines for ML models and data workflows
  • Collaborate with cross-functional teams to build scalable and robust ML infrastructure on cloud and on-premises environments
  • Monitor and optimize model performance and infrastructure to ensure efficient resource usage
  • Manage data versioning and model versioning across multiple environments
  • Implement security, governance, and compliance protocols in ML deployment and data pipelines
  • Support troubleshooting, debugging, and incident management for ML infrastructure issues

Requirements:

  • 4 to 10 years of experience in MLOps, DevOps, or ML Engineering
  • Strong proficiency with cloud platforms such as AWS, Azure, or GCP
  • Experience with containerization and orchestration tools like Docker and Kubernetes
  • Hands-on experience with ML model deployment, monitoring, and scaling
  • Proficiency with CI/CD tools such as Jenkins or GitLab CI
  • Familiarity with data versioning and management tools such as DVC
  • Strong coding skills in Python with knowledge of ML libraries like TensorFlow or PyTorch
  • Strong problem-solving skills and ability to work in a collaborative environment
  • Effective communication skills for cross-functional teamwork

Nice to have:

  • Experience with MLOps frameworks such as MLflow or Kubeflow
  • Knowledge of data engineering best practices and data pipeline tools like Apache Airflow or Kafka
  • Certification in any cloud platform such as AWS, Azure, or GCP
What we offer:
  • Competitive compensation
  • Opportunity to work with a dynamic team on cutting-edge AI and ML solutions
  • Professional growth and development opportunities

Additional Information:

Job Posted:
December 26, 2025

Employment Type:
Fulltime
Work Type:
On-site work
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