Description

You will develop, deploy, and maintain predictive and prescriptive machine learning models in production environments.

This role is on-site.

Responsibilities

• Design, train, and optimize ML models for classification, regression, clustering, and forecasting.
• Build and maintain scalable ML pipelines for training, evaluation, and deployment using Python and Jenkins.
• Analyze large, complex datasets to extract actionable insights and drive business decisions.
• Implement MLOps practices including model versioning, monitoring, and automated retraining strategies.
• Collaborate with cross-functional teams to define use cases and document model methodologies and results.

Required Skills

• 6+ years of experience in AI/ML model development and deployment.
• Strong proficiency in Python for data manipulation, model building, and automation.
• Hands-on experience with GCP Vertex AI, AWS SageMaker, or Azure ML.
• Experience with Jenkins and CI/CD pipelines for ML workflows.
• Deep understanding of machine learning tasks and statistical techniques.
• Ability to analyze complex datasets and interpret model outputs for stakeholders.
• Familiarity with MLOps principles for model lifecycle management.

Preferred Skills

• Experience with Snowflake or other cloud data warehouses.
• Strong documentation and reporting skills for technical methodologies.

Key Skills

Education

Any Graduate