Senior Software Engineer
Current• Design, develop, and deploy generative AI applications leveraging RAG architectures and tools (e.g., LangChain and Pandas AI)• Integrate pre-trained language models (e.g., GPT-3.5, GPT-4, BERT) with specialized data sources (structured and unstructured) to enable context-aware text generation and prompt-answering capabilities.• Optimize application performance by fine-tuning language models, improving retrieval algorithms, and implementing caching mechanisms.• Knowledge of vector databases e.g., Pinecone, Faiss, & Chroma. • Implement efficient data retrieval and indexing mechanisms to support fast and accurate information retrieval from large-scale datasets.• Experiment with different model architectures, training techniques, and hyperparameters to improve LLM performance.• Familiarity with popular Python libraries for AI, such as NumPy, Pandas.• Experience in text preprocessing techniques such as tokenization, lemmatization, and part-of-speech tagging using spaCy and NLTK.• Understanding of fundamental machine learning concepts and algorithms, particularly in regression and classification.• Experience in building and evaluating regression models for prediction tasks.• Familiarity with semantic technologies such as RDF (Resource Description Framework), OWL (Web Ontology Language), and SPARQL (SPARQL Query Language).• Ability to design and implement ontologies and vocabularies to model domain-specific knowledge and relationships.• Experience in integrating and aligning data from multiple sources to create a unified knowledge graph.• Knowledge of graph databases and triple stores, such as StarDog, & Neo4j for storing and querying knowledge graphs.• Define communication interface between machine & MES.• Develop MES Specification & Configuration.• Conduct Pre acceptance & final release of MES Standards.
