The AI/ML Engineer is responsible for designing, building, and deploying intelligent systems that enable predictive insights, automation, and smarter decision-making across the enterprise. This individual operates at the intersection of data science, software engineering, and applied research — translating complex business problems into scalable machine learning solutions that deliver measurable impact.

Key Responsibilities:

• Develop, train, and optimize machine learning and deep learning models using Python, R, TensorFlow, and PyTorch.
• Partner with product, engineering, and data teams to identify opportunities where AI can drive efficiency or innovation.
• Build end-to-end ML pipelines, from data ingestion and feature engineering to model deployment and monitoring.
• Ensure responsible AI practices through bias detection, model explainability, and continuous model retraining.
• Stay current on emerging trends in generative AI, NLP, and computer vision to drive future capabilities.

Ideal Background:

• 5–10 years of experience in applied AI/ML
• Strong foundation in statistics, algorithms, and data engineering.
• Proven success deploying models in production environments (e.g., AWS Sagemaker, Azure ML).
• Advanced degree in Computer Science, Data Science, or related field preferred.