Machine Learning Ops (MLOps) Engineer

Job Title: MLOps Engineer
Location: Noida, Uttar Pradesh
Experience Required: 8–12 Years
Working Days: 5 Days / Week
Notice Period: Maximum 15 Days

Job Overview

We are hiring a Senior MLOps Engineer with strong experience in building and managing production-grade ML platforms and scalable data pipelines. The ideal candidate should have deep expertise in AWS, Apache Airflow, Apache Spark, Kubernetes, and ML lifecycle automation.

Mandatory Requirements

• 8+ years of DevOps experience with at least 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years of hands-on experience with Apache Airflow / AWS MWAA in production environments
• 4+ years of hands-on experience with Apache Spark (EMR / Glue / managed clusters)
• Strong AWS expertise including:
• EKS, ECS, Fargate, EC2, Lambda
• EMR, Glue, S3, Redshift, Athena, RDS, Kinesis
• CloudWatch monitoring
• Strong Python experience for pipeline and automation development
• 4+ years of recent AWS cloud experience
• Product company experience preferred (strong service profiles with deep AWS + MLOps expertise may be considered)

Preferred Skills

• Docker deployments for ML workflows on EKS / ECS
• ML observability (data drift, model drift, monitoring, alerting using CloudWatch / Grafana / Prometheus / OpenSearch)
• CI/CD/CT using GitHub Actions or Jenkins
• Experience with JupyterHub, metadata tracking, Linux scripting
• Understanding of ML frameworks such as TensorFlow or PyTorch for deployment scenarios

Key Responsibilities

• Design and manage cloud-native ML platforms for training and inference
• Build ML/ETL pipelines using Apache Airflow / MWAA
• Develop distributed data workflows using Apache Spark
• Containerize and deploy ML workloads using Docker and Kubernetes (EKS / ECS / Fargate)
• Implement CI/CD pipelines for automated model validation, testing, and deployment
• Enable ML observability including drift detection and performance monitoring
• Ensure governance, reproducibility, and secure data pipelines
• Collaborate with data science and engineering teams to productionize models

Job Type: Full-time

Pay: ₹6,000,000.00 - ₹8,000,000.00 per year

Work Location: In person