AI System Engineer

Essential Skills: Machine Learning & Deep Learning: Solid understanding of ML concepts and hands-on experience with deep learning (especially neural networks and Transformers). Python Programming: Strong Python coding skills with familiarity in frameworks like TensorFlow, PyTorch, or Keras. Natural Language Processing (NLP): Experience with tokenization, embeddings, and language model fine-tuning. Data Engineering: Ability to clean, process, and manage large datasets with a focus on data quality. Math & Statistics: Good knowledge of linear algebra, calculus, probability, and statistics. Preferred Additional Skills: Model Deployment (MLOps): Exposure to deploying models using Docker, APIs, CI/CD, and tools like MLflow or Hugging Face Hub. RAG & LLM Integration: Hands-on with FAISS, LangChain, embedding models, and large language models. Prompt Engineering: Skilled in designing prompts and evaluating AI output quality. System Scalability: Understanding of GPU optimization and AI system performance.