AI/ML Training Pipeline Engineer Internship

Key Responsibilities

• Design, develop, and maintain end‑to‑end AI/ML training pipelines that support large‑scale model training.
• Implement attention‑based architectures and integrate them into existing deep‑learning workflows.
• Generate synthetic and augmented datasets to improve model robustness and coverage.
• Apply advanced data‑preprocessing techniques, including cleaning, normalization, and feature engineering.
• Collaborate with data scientists and ML engineers to optimize pipeline performance and reduce training latency.
• Document pipeline components and provide reproducible code for future use.

Requirements

• Strong programming skills in Python and familiarity with deep‑learning libraries such as PyTorch or TensorFlow.
• Solid understanding of attention mechanisms and their application in neural networks.
• Experience with data‑generation, augmentation, and preprocessing pipelines.
• Ability to work independently and in a fast‑paced, collaborative environment.
• Excellent communication skills and a passion for cutting‑edge AI research.