Artificial Intelligence Lead

• Build scalable data pipelines and automate model training, validation, and deployment workflows.
• Optimize model performance, latency, and accuracy using modern techniques.
• Work closely with cross-functional teams including Data Engineering, Product, and Software Engineering.
• Perform exploratory data analysis, feature engineering, and experiment tracking.
• Integrate AI models into applications using APIs, microservices, or cloud-based solutions.
• Stay updated with the latest advancements in AI, ML, and GenAI technologies.

Requirements

• Strong proficiency in Python, ML libraries (NumPy, Pandas, Scikit-learn), and DL frameworks (TensorFlow/PyTorch).
• Experience with LLMs, NLP, transformers, embeddings, and prompt optimization.
• Knowledge of MLOps tools like MLflow, Kubeflow, Airflow, or similar.
• Experience in using cloud platforms (AWS / Azure / GCP) for AI model deployment.
• Hands-on experience with vector databases, feature stores, or model registries (nice to have).
• Familiarity with API development, microservices architecture, and containerization (Docker, Kubernetes).
• Strong understanding of algorithms, data structures, and model evaluation techniques.