Architect(Generative AI & LLM expert)

As a Generative AI & LLM expert, you will be a valuable member of our AI and ML team, responsible for designing, developing, fine-tuning, and deploying large language models and generative AI applications. This role offers a unique opportunity to work with cutting-edge AI technologies and enhance your skills in machine learning, natural language processing, and deep learning. Your main responsibilities will include architecting robust systems to integrate LLMs and support retrieval workflows, providing guidance on the use of Vector DBs and model deployment on cloud platforms, optimizing the fine-tuning process for business-specific LLM use cases, and designing applications with on-premise/cloud-based LLM, RAG, and Langchain. Key Skills: - Model Training & Fine-Tuning: Assist/Build in training and fine-tuning large language models on domain-specific data. - Data Preparation & Preprocessing: Work with large datasets, perform data cleaning, tokenization, and prepare text data for model training. - Prompt Engineering: Experiment with and refine prompt techniques for various generative AI applications. - Model Evaluation & Optimization: Evaluate models using metrics such as BLEU, ROUGE, and perplexity, and optimize models for performance. - Collaborate with Cross-functional Teams: Work closely with engineering and product teams to develop scalable AI solutions. - Documentation & Reporting: Document processes, model architectures, and code; create model cards and write reports for stakeholders. - Managing and training LLM models and generating embeddings for semantic search via Vector DBs. Qualifications: - Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related field. Proximate Role And Experience: - Proximate Role: Architect with MLOps experience. - Experience Level: 7+ years in building ML pipelines, feature engineering, or deploying models/LLMs on cloud platforms. Proximate Skills Considered: - Experience with machine learning pipelines, model optimization, and feature engineering. - Proficiency in database indexing (e.g., Elasticsearch) or data retrieval methods. - Familiarity with deploying ML models in cloud environments and optimizing model inference. Innate Skills: - Leadership skills to mentor and guide teams in adopting new technologies. - Strategic thinking to align AI implementations with business objectives.,