MLOps Engineer

Job Title: MLOps Engineer (Senior)

Location: Noida, Uttar Pradesh (Office / On-site)
Experience: 8–12 Years
Work Mode: Work from Office (5 days a week)
Positions Open: 1

Job Description

We are hiring a Senior MLOps Engineer to design, build, and manage production-grade machine learning platforms and pipelines. The role involves close collaboration with data science, data engineering, and platform teams to operationalise and scale ML models in a cloud-native environment.

Key Responsibilities

• Design and manage cloud-native ML platforms for training, inference, and lifecycle automation
• Build and maintain ML and ETL pipelines using Apache Airflow / AWS MWAA
• Develop distributed data processing workflows using Apache Spark (EMR / Glue)
• Containerise and deploy ML workloads using Docker, Kubernetes (EKS), ECS, Fargate, and AWS Lambda
• Implement CI/CD/CT pipelines for model validation, training, testing, and deployment
• Set up ML observability including data drift, model drift, performance monitoring, and alerting
• Ensure data governance, versioning, metadata tracking, and reproducibility
• Support productionisation of notebooks, experiments, and ML models

Mandatory Requirements

• 8+ years of overall DevOps experience with 4+ years in MLOps and ML pipeline automation
• Strong hands-on experience with Apache Airflow / MWAA in production environments
• 4+ years of hands-on experience with Apache Spark (EMR / Glue / managed or self-hosted)
• Strong experience across AWS services including EKS, ECS, Fargate, Lambda, S3, Kinesis, Athena, Redshift, and CloudWatch
• Strong Python skills for automation and pipeline development
• Recent and hands-on AWS cloud experience
• Product company background preferred (strong service-company profiles with deep MLOps and AWS expertise may be considered)

Preferred Skills

• Docker-based ML deployments on EKS or ECS
• Experience with ML observability tools such as CloudWatch, Grafana, Prometheus, OpenSearch
• CI/CD experience using GitHub Actions or Jenkins
• Experience with JupyterHub, Linux, scripting, and ML lifecycle tooling
• Understanding of ML frameworks such as TensorFlow or PyTorch for deployment scenarios

Education

Master’s degree in Computer Science, Machine Learning, Data Engineering, or a related field.

Job Type: Full-time

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

Work Location: In person