MLOPS Engineer - Mumbai, India - Getinz Techno Services

Description

We are hiring for leading Data Analytics company, based out in Mumbai & Pune.

Experience Range: - 8 years.

Please note:
Immediate or serving Notice period will be preferable.


Location:
Pune/Mumbai


Skills:
MLOPs, AWS Sagemaker / Azure ML,


ELK, DockerSkills and Qualifications:
Strong proficiency in Azure ML, DataBricks, ML Flow, and AWS Sagemaker for model development and deployment.

Proficiency in DevOps practices, CI/CD pipelines, version control systems (e.g., GitHub), and automation using tools like GitHub Actions and YAML.

Experience with infrastructure as code tools such as Terraform for provisioning and managing cloud resources.

Expertise in containerization technologies like Docker and orchestration tools like Kubernetes for deploying and managing applications.

Knowledge of monitoring and observability tools such as Prometheus, Grafana, and ELK stack for tracking performance metrics and logs.

Familiarity with machine learning concepts and the ability to work closely with data scientists to operationalize models effectively.

Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.


Roles & Responsibilities:
Collaborate with data scientists, engineers, and other stakeholders to streamline the machine learning model deployment process.

Design, build, and maintain CI/CD pipelines for machine learning model deployment and automation using tools like GitHub Actions, YAML, and Terraform.

Implement containerization strategies and manage Docker-based deployments for machine learning models.

Utilize Kubernetes for orchestration and management of containerized applications.

Develop and maintain monitoring and alerting systems using Prometheus, Grafana, and ELK stack to ensure the health and performance of deployed models.

Implement and manage machine learning infrastructure on cloud platforms such as Azure ML and AWS Sagemaker.

Continuously optimize and improve MLOps workflows for scalability, reliability, and efficiency.


Education and Experience:
Bachelor's or Master's degree in Computer Science, Engineering, or related field.

Minimum of X years of experience in MLOps, DevOps, or a similar role within the machine learning domain.

Relevant certifications in Azure, AWS, Kubernetes, or other related technologies are a plus.