*Strong knowledge of Pattern Recognition and Neural Networks**
Solid foundation in Computer Science and Algorithms
*Proficiency in Statistics and machine learning concepts**
Experience in deploying machine learning models in production environments
*Strong understanding of NLP techniques (Tokenization, Embeddings,Transformers, Attention Mechanisms).**
Proficiency in SQL and experience handling large datasets.
*Good to have**
*GenAI Stack: Experience with frameworks like LangChain, LlamaIndex, orHaystack.** Vector Databases: Hands\-on experience with vector stores such as Pinecone,Milvus, Weaviate, ChromaDB or FAISS.
*Model Tuning: Proven track record of fine\-tuning open\-source models (e.g.,Hugging Face transformers) on custom datasets.**
Cloud AI: Experience with AWS SageMaker, Azure AI Studio, or GoogleVertex AI.
*Big Data: Experience handling large\-scale datasets using Apache Spark orDatabricks.**
*Soft Skills \& Competencies:**
Problem Solver: Ability to break down ambiguous problems into solvablealgorithmic components.
*Continuous Learner: The AI landscape changes weekly; you must demonstratea hunger to keep up with the latest papers and techniques.**
Communication: Ability to explain complex model behaviors to non\-technicalstakeholders.