Language Model Architect

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 : Large Language Models (LLMs)
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary:
As a Senior GenAI Engineer, you will lead the design, development, and deployment of sophisticated AI solutions that leverage both traditional machine learning and cutting-edge generative AI techniques. You will apply your deep expertise in ML engineering, large language models (LLMs), retrieval-augmented generation (RAG), and orchestration frameworks to build scalable, production-ready AI applications. This role bridges advanced machine learning with GenAI innovation, ensuring both technical rigor and significant business impact.

Key Responsibilities:
Lead the design and implementation of applications powered by LLMs, multimodal models, and generative architectures.
Fine-tune foundation models (e.g., with LoRA, PEFT) for domain-specific use cases.
Architect and optimize retrieval-augmented generation pipelines using vector databases (eg FAISS, Pinecone, Weaviate).
Guide integration of APIs and frameworks (LangChain, LlamaIndex, Semantic Kernel) into production systems.
Develop and deploy predictive ML models using frameworks such as PyTorch, TensorFlow, and Scikit-learn.
Build and maintain scalable data pipelines in collaboration with data engineers.
Implement and advocate for best MLOps practices related to automation, monitoring, CI/CD, and model retraining.
Design and refine evaluation frameworks for both predictive and generative models, focusing on accuracy, fairness, hallucination detection, and grounding.
Establish and continually improve monitoring systems for live models to ensure reliability and performance.
Work with cross-functional teams to align AI solutions with business goals and technical requirements.
Communicate advanced ML/GenAI concepts effectively to non-technical stakeholders for strategic alignment.

Professional & Technical Skills:-
AWS Sagemaker, Foundation Models, Evaluation, LLM Prompting, RAG, Vector databases, Python, Agentic, ML frameworks (e.g. LangChain, PyTorch, Scikit-learn), Architecture Design, Security Concepts.
Working experience in Bedrock, Foundation Models, Evaluation, LLM Prompting, RAG, Python, Agentic AI.
Extensive experience (15+ yrs) with 3 4 yrs hands on experience in Gen AI.