Full Time
MLOps Engineer
- JOB CODE :
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Mumbai, Pune, Nagpur, Indore, Vadodara, Ahmedabad, Hyderabad, Chennai, Warangal, Vishakhapatnam, Vijayawada, Bangalore, Kochi, Kolkata, Bhubaneswar, Coimbatore, Chandigarh, Delhi, Gurgaon, Noida, Jaipur
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Job Description :
We are actively seeking a highly skilled MLOps Engineer with a strong background in Machine Learning, Python, Deep Learning, and expertise in containerization technologies such as Docker & Kubernetes. The successful candidate will be responsible for deploying and maintaining machine learning models in production, ensuring scalability, reliability, and efficiency. This position is open for multiple locations across India.
Duties & Responsibilities:
Machine Learning Deployment:
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Deploy and manage machine learning models in production environments. -
Collaborate with data scientists and software engineers to operationalize models effectively.
MLOps Automation:
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Develop and implement automation scripts for model deployment and monitoring. -
Implement continuous integration and continuous deployment (CI/CD) pipelines for machine learning workflows.
Containerization:
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Utilize Docker for packaging and containerizing machine learning applications. -
Manage and orchestrate containers using Kubernetes for scalability and resilience.
Infrastructure as Code (IaC):
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Implement Infrastructure as Code practices for provisioning and managing infrastructure resources. -
Ensure consistency and repeatability in deploying machine learning infrastructure.
Monitoring and Scaling:
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Implement monitoring solutions for tracking model performance and system health. -
Scale machine learning infrastructure to handle varying workloads efficiently.
Collaboration:
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Work closely with data scientists, developers, and operations teams to bridge the gap between development and operations. -
Collaborate with stakeholders to understand business requirements and translate them into operational solutions.
Security and Compliance:
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Implement security measures for machine learning systems and ensure compliance with data privacy regulations. -
Perform regular security audits and implement best practices for securing machine learning pipelines.
Minimum Qualifications:
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Bachelor’s degree in Computer Science, Information Technology, or a related field. -
Minimum of 5 years of experience in MLOps, with a focus on deploying and managing machine learning models. -
Strong programming skills in Python and experience with deep learning frameworks. -
Hands-on experience with Docker and Kubernetes in a production environment. -
Familiarity with Infrastructure as Code tools such as Terraform. -
Solid understanding of machine learning concepts and workflows. -
Experience with CI/CD pipelines for machine learning workflows. -
Excellent problem-solving and analytical skills. -
Effective communication and collaboration skills.
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