Large Language Model Architect

Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Python (Programming Language)
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary: We are looking for an experienced and highly skilled Python + Gen AI Full Stack Engineer with 8–10 years of professional experience in software engineering, specializing in machine learning, large language models (LLMs), and generative AI technologies. The ideal candidate will possess deep technical expertise in Python front-end and back-end development, end-to-end AI/ML solution design, and large-scale model deployment. The role requires strong problem-solving abilities, architectural vision, and hands-on experience with state-of-the-art Gen AI tools and frameworks. Roles & Responsibilities: 1. Design, develop, and maintain scalable AI-driven applications using Python and front-end technologies. 2. Architect and implement full-stack solutions integrating LLMs and generative AI capabilities. 3. Build and fine-tune large language models (OpenAI, Hugging Face Transformers, etc.) for various enterprise applications. 4. Collaborate with data scientists and product teams to define AI use cases, prototypes, and production-grade deployments. 5. Integrate APIs and develop microservices to enable LLM-based features in web applications. 6. Manage model lifecycle, including training, evaluation, versioning, and deployment. 7. Implement best practices for data preprocessing, vector databases, embeddings, and prompt engineering. 8. Ensure performance, scalability, and security of AI applications. 9.Stay current with Gen AI trends, research, and emerging tools in the AI/ML ecosystem. 10.Conduct code reviews, mentor junior developers, and contribute to technical documentation and architecture planning. Professional & Technical Skills: 1.Languages & Frameworks: Expert in Python, Fast API, Flask, Django; Proficient in HTML, CSS, JavaScript, React or Vue.js. 2. Machine Learning & Deep Learning: Strong understanding of supervised/unsupervised learning, model training, feature engineering, PyTorch, TensorFlow. Generative AI & LLMs: 3. Hands-on experience with OpenAI API, Lang Chain, Hugging Face Transformers, and Retrieval-Augmented Generation (RAG). 4. Proficient in prompt engineering, embeddings (e.g., FAISS, Pinecone), and vector stores. 5. Experience in fine-tuning LLMs and integrating them into enterprise applications. 6. DevOps & Deployment: Docker, Kubernetes, CI/CD pipelines, REST APIs, Git. 7. Data Technologies: Pandas, NumPy, SQL, NoSQL (MongoDB, Redis), data pipelines. 8. Cloud Platforms: Azure, AWS, or GCP for model training, serving, and scalable infrastructure. 9. MLOps Tools: MLflow, Weights & Biases, or similar platforms for model monitoring and experimentation tracking. Software Development Best Practices: Agile methodologies, unit testing, TDD, code versioning, architectural design patterns. Additional Information: 1. bachelor’s or master’s degree in computer science.