Machine Learning Engineer_5+ Years

Zorba AI; Gurugram District; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Zorba AI is looking for a Machine Learning Engineer in Gurugram to build and deploy scalable machine learning solutions. The role entails managing the end-to-end ML lifecycle including model development, deployment, monitoring, and optimization. Ideal candidates should have strong experience with Python and SQL, hands-on MLOps skills, and familiarity with CI/CD tools and Docker. This is an exciting opportunity to work in a collaborative environment with Data Engineers and Data Scientists.

Qualifications

• Strong experience in Python and SQL.
• Hands-on experience with Machine Learning & MLOps.
• Experience with MLflow/model registry tools.
• Good knowledge of Apache Spark/DataFrames.
• Experience in CI/CD tools (Azure DevOps/GitHub Actions).
• Hands-on with Docker (Kubernetes is a plus).
• Cloud experience in Microsoft Azure.

Responsibilities

• Develop, deploy, and maintain machine learning models in production.
• Build and manage ML pipelines for training and inference.
• Convert Data Science models into production-ready solutions.
• Implement feature engineering pipelines and feature stores.
• Monitor model performance (data drift, accuracy, degradation).
• Implement CI/CD pipelines for ML workflows.
• Collaborate with Data Engineers, Data Scientists, and DevOps teams.

Skills

Python

SQL

Machine Learning

MLOps

MLflow

Apache Spark

CI/CD tools

Docker

Kubernetes

Microsoft Azure

Tools

MLflow

Docker

Azure DevOps

GitHub Actions

Job description

Job Description

We are hiring a Machine Learning Engineer with strong experience in building and deploying scalable ML solutions. The candidate will be responsible for end-to-end ML lifecycle including model development, deployment, monitoring, and optimization.

Key Responsibilities

• Develop, deploy, and maintain machine learning models in production
• Build and manage ML pipelines for training, batch, and real-time inference
• Convert Data Science models into production-ready solutions
• Implement feature engineering pipelines and feature stores
• Work on model deployment using Docker, APIs, or cloud services
• Monitor model performance (data drift, accuracy, degradation)
• Implement CI/CD pipelines for ML workflows
• Collaborate with Data Engineers, Data Scientists, and DevOps teams

Required Skills (Must Have)

• Strong experience in Python and SQL
• Hands-on experience with Machine Learning & MLOps
• Experience with MLflow / model registry tools
• Good knowledge of Apache Spark / DataFrames
• Experience in CI/CD tools (Azure DevOps / GitHub Actions)
• Hands-on with Docker (Kubernetes is a plus)
• Cloud experience in Microsoft AzureExperience in model deployment & monitoring

Good to Have

• Knowledge of TensorFlow / PyTorch
• Understanding of Deep Learning concepts
• Experience in feature engineering & model evaluation
• Exposure to Databricks

Skills: pipelines, machine learning, ml engineer