Description

You will lead the design, development, and optimization of AI/ML systems in production.

This role is on-site.

Responsibilities

• Design and optimize complex data pipelines using ML engineering best practices for scalability.
• Implement MLOps pipelines to manage deployment, monitoring, and lifecycle of AI/ML models.
• Diagnose data quality issues, maintain pipelines, and document technical assumptions.
• Collaborate with data scientists to validate datasets and document features accurately.
• Maintain model monitoring scripts, investigate alerts, and coordinate resolutions.

Required Skills

• 7+ years of relevant experience in AI, ML, or Data Engineering.
• 3+ years of hands-on experience building ETL pipelines using AWS services.
• Proficiency in Python and familiarity with key machine learning frameworks.
• Experience developing and implementing ML pipelines for production model deployment.
• Strong understanding of cloud technologies, specifically AWS SageMaker.
• Knowledge of the Machine Learning Development Life Cycle (MDLC) and AI engineering best practices.
• Experience designing end-to-end machine learning pipelines and solution architectures.

Preferred Skills

• Bachelor's or Master's degree in Computer Science or related field.

Key Skills

Education

Bachelor's or Master's degrees