Machine Learning Engineer

Location: Bangalore (Hybrid)

Responsibilities

• Design, develop, and implement machine learning models and algorithms to solve

complex business problems.

• Collaborate with data scientists to transition models from research and development to

production-ready systems.

• Build and maintain scalable data pipelines for ML model training and inference using

Databricks.

• Implement and manage the ML model lifecycle using MLflow for experiment tracking,

model versioning, and model registry.

• Deploy and manage ML models in production environments on Azure, leveraging

services like Azure Machine Learning, Azure Kubernetes Service (AKS), or Azure

Functions.

• Support MLOps workloads by automating model training, evaluation, deployment, and

monitoring processes.

• Ensure the reliability, performance, and scalability of ML systems in production.
• Monitor model performance, detect drift, and implement retraining strategies.
• Collaborate with DevOps and Data Engineering teams to integrate ML solutions into

existing infrastructure and CI/CD pipelines.

• Document model architecture, data flows, and operational procedures.

Qualifications

• Education: Bachelors or Masters Degree in Computer Science, Engineering, Statistics,

or a related quantitative field.

• Experience: Minimum 3+ years of professional experience as an ML Engineer or in a

similar role.