MLOps Engineer

Location: Bangalore / Pune / Gurgaon
Experience: 5-7 Years
Notice Period: Immediate Joiners Preferred

Key Responsibilities

- Support end-to-end ML model lifecycle including deployment, monitoring, optimization, and production support.
- Implement and maintain MLOps frameworks for scalable and reliable model operations.
- Work with data science and engineering teams to operationalize AI/ML solutions.
- Ensure model governance, monitoring, and compliance across environments.

Required Skills

- Solid experience in MLOps and Machine Learning lifecycle management.
- Hands-on experience in Python and PySpark.
- Experience with Hadoop ecosystem (HDFS, Hive, Spark).
- Exposure to AWS and/or Databricks platforms.
- Understanding of data pipelines, feature engineering, and large-scale data processing.




- Experience supporting ML models across Development, UAT, and Production environments.

Good to Have

- MLflow, Airflow, Docker.
- CI/CD tools such as Jenkins, GitLab, Git-based workflows.
- AWS services: S3, IAM, CloudWatch, EMR, Glue.
- Knowledge of data lakes, data warehouses, and distributed storage systems.
- Experience in model monitoring, performance tracking, data governance, and model governance.

Ideal Candidate: Strong MLOps professional with experience in cloud-native ML deployments, Databricks/AWS ecosystem, and scalable data engineering environments.

📌 MLops - AWS & Pyspark-Immediate joiners only (Pune)
🏢 EY
📍 Pune