Artificial Intelligence Engineer

Role & responsibilities

• • Programming Languages -
• .Python (primary for AI/ML): TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy
• . R (for statistical modeling)
• . Optional: Java, C++, or Julia for performance-critical tasks • Machine Learning & AI
• . Supervised & Unsupervised Learning (classification, regression, clustering)
• Deep Learning (CNNs, RNNs, Transformers)
• . Natural Language Processing (NLP): Tokenization, embeddings, LLM fine-tuning
• Generative AI: Prompt engineering, model deployment
• • Mathematics & Statistics
• .Linear algebra, calculus, probability, and optimization o Statistical inference and hypothesis testing
• • Data Engineering & Preprocessing
• . Data cleaning, feature engineering, and handling large datasets
• Familiarity with PySpark or Spark MLlib for distributed ML
• • Model Deployment & MLOps Containerization (Docker, Kubernetes)