Senior Data & AI/ MLOps Engineer

Core Requirements:

• 7+ years of total IT experience, including at least 3 years in MLOps.
• Experience designing and implementing MLOps pipelines using:
• MLflow, Apache Airflow
• CI/CD tools
• Configuration tools: Ansible, Terraform
• Strong proficiency in:
• Python, PySpark, SQL
• Machine Learning (ML), Deep Learning, NLP
• Cloud: AWS (preferred), but Azure acceptable
• AWS tools: SageMaker, BedRock, EC2, Lambda, S3, Glue Tables
• DataBricks
• Solid knowledge of:
• ML lifecycle: Data ingestion → Training → Deployment → Monitoring
• Containerization, Versioning
• ML model deployment and monitoring
• Experience working with models using RNN, CNN, GNN, GAN

Role Responsibilities:

• Build and maintain robust MLOps pipelines
• Automate testing, validation, and deployment of models
• Work with Data Scientists to translate prototypes into production
• Optimize ML code and monitor performance
• Collaborate with:
• Data Scientists
• Data Engineers
• Architects
• Document processes and workflows
• Communicate effectively with technical teams

Preferred Experience (Nice-to-Have):

• Exposure to both AWS and Azure (AWS preferred)
• Familiarity with AI/ML Ops as a primary skillset
• Infrastructure Ops as a secondary skill

Soft Skills:

• Strong communication skills (verbal and written)
• Ability to interpret data/metrics
• Analytical mindset
• Team collaboration

Job Type: Full-time

Pay: ₹100,000.00 - ₹200,000.00 per month

Experience:

• ML Ops: 7 years (Required)
• Python, PySpark, SQL: 7 years (Required)
• Machine Learning (ML), Deep Learning, NLP: 7 years (Required)
• AWS tools: SageMaker, BedRock, EC2, Lambda, S3, Glue Tables: 7 years (Required)
• Databricks: 7 years (Required)

Work Location: In person