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MLOps Engineer – Databricks

MLOps Engineer – Databricks

Scouto AI

0 years

12 - 14 Lacs

pune maharashtra india

Posted:1 week ago| Platform:

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Skills Required

databricks support deployment learning aws ml model development monitoring data design jenkins automate sonarqube code checks pipeline storage versioning management engineering transitions bitbucket strategies collaborative reliability troubleshooting debugging automation governance training configuration maintenance metrics python modification analyze mlflow containerization docker kubernetes azure technology software

Work Mode

On-site

Job Type

Full Time

Job Description

Job Summary

We are seeking a skilled

MLOps Engineer

with hands-on experience in

Databricks

and

CI/CD automation

to support the deployment and operationalization of machine learning models. The ideal candidate should possess a strong understanding of

AWS services

Jenkins

SonarQube

, and

Bitbucket

, along with basic proficiency in

Python

and a good grasp of the

ML lifecycle

Key Responsibilities

Manage and support end-to-end MLOps workflows for model development, deployment, and monitoring.
Work extensively on Databricks for building and managing ML pipelines, data workflows, and model execution.
Design and maintain CI/CD pipelines using Jenkins to automate ML model deployments.
Integrate SonarQube for code quality checks and ensure bug-free ML and data pipeline code.
Manage AWS services, including S3 buckets, for model storage, versioning, and artifact management.
Collaborate closely with Data Science and Data Engineering teams to ensure smooth transitions of models from development to production.
Utilize Bitbucket for version control, branching strategies, and collaborative code development.
Review and modify deployment scripts or configurations to enhance reliability and performance.
Participate in troubleshooting, debugging, and continuous improvement of MLOps processes.
Ensure adherence to best practices in code quality, automation, and deployment governance.

Required Skills

Databricks (Mandatory): Strong hands-on experience with data pipelines, model training, and deployment workflows.
Jenkins: Practical knowledge of CI/CD pipeline setup, configuration, and maintenance.
AWS (S3 Buckets): Experience managing model artifacts, datasets, and configurations.
SonarQube: Understanding of code quality metrics and best practices for bug fixing.
Bitbucket (Important): Proficiency in version control and branching strategies for collaborative projects.
Python (Optional): Basic understanding for reading and modifying ML-related scripts.
Modification Understanding: Ability to analyze and adapt existing workflows, pipelines, or configurations as per project needs.

Good to Have

Familiarity with ML lifecycle management tools such as MLflow.
Understanding of containerization technologies (e.g., Docker, Kubernetes) for ML model deployment.
Experience working in cloud-based MLOps environments (AWS / Azure).

Education

Bachelor’s degree in Computer Science, Information Technology, or a related field.

Skills: python software foundation,pipelines,docker,bitbucket,aws,s3,sonarqube,databrick,jenkins,kubernetes,mlops,mlflow

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MLOps Engineer – Databricks