MLOps Engineer

Code1 Tech Systems; India; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Code1 Tech Systems in India is seeking an MLOps Engineer with 6–8 years of experience to support the migration of ML models to Azure Databricks. The role involves building and maintaining CI/CD pipelines and collaborating with Data Engineering teams to ensure efficient data movement.

The ideal candidate should possess strong skills in Azure Databricks, PySpark, and MLflow, along with a track record of optimizing performance and debugging. Join a vibrant team to innovate enterprise technology.

Qualifications

• 6–8 years of experience in MLOps or related field.
• Strong hands-on expertise in Azure Databricks.
• Advanced skills in PySpark development and optimization.

Responsibilities

• Support migration of ML models from GCP to Azure Databricks.
• Build and maintain CI/CD pipelines using GitHub Actions.
• Implement MLflow for model tracking and lifecycle management.
• Collaborate with Data Engineering teams for data movement strategies.

Skills

Azure Databricks

PySpark

CI/CD pipelines

MLflow

Terraform

GCP

Azure

Debugging

Performance optimization

Job description

At Code1 Tech, we drive innovations that shape the future of enterprise technology. Our expertise spans Data Engineering, AI/ML, Cloud Solutions, and Full‑Stack Development. We empower businesses with cutting‑edge technology solutions, enabling digital transformation at scale. Join us to build impactful products with a passionate team of engineers and innovators.

Experience: 6–8 Years

About the Role

The client currently operates Data Science workloads in GCP and is migrating these workloads to Azure Databricks. Input data will continue to originate from GCP, Data Science processing will execute in Azure Databricks, and outputs will be written back to GCP. The MLOps Engineer will play a critical role in model migration, workflow automation, CI/CD implementation, model lifecycle management, and cross‑cloud data movement initiatives.

Key Responsibilities:

• Support migration of existing ML models from GCP to Azure Databricks.
• Analyze, replicate, and optimize existing Data Science model architectures.
• Build and maintain CI/CD pipelines using GitHub Actions.
• Implement and manage MLflow for model tracking, versioning, and lifecycle management.
• Develop scalable Data & ML pipelines using Databricks and PySpark.
• Collaborate with Data Engineering teams on GCP to Azure Databricks data movement strategies.
• Build pipelines to move model outputs from Azure Databricks back to GCP.
• Provide architectural guidance and workflow optimization recommendations.
• Improve testing coverage, monitoring, observability, and performance tuning.
• Drive cost optimization and operational efficiency initiatives.

Mandatory Technical Skills:

• Strong hands‑on expertise in Azure Databricks with deep understanding of Databricks internals.
• Advanced PySpark development, optimization, and execution plan analysis.
• Experience building CI/CD pipelines using GitHub Actions.
• Strong experience with MLflow for model tracking, deployment, and lifecycle management.
• Knowledge of Terraform and Databricks infrastructure automation.
• Experience integrating workflows across GCP and Azure cloud platforms.
• Strong debugging, troubleshooting, and performance optimization capabilities.
• Experience operationalizing Machine Learning models in production environments.
• Cost optimization mindset for cloud and data processing workloads.

Good to Have

• Experience with cross‑cloud data movement architectures.
• Understanding of Data Science model structures and workflows.
• Exposure to model monitoring, observability, and alerting frameworks.
• Experience collaborating closely with Data Science teams.