We are seeking a highly skilled Machine Learning Engineer with hands-on experience in Large Language Models (LLMs) and Generative AI technologies. The ideal candidate will have expertise in building, fine-tuning, and deploying LLM-based solutions, along with strong programming skills and a deep understanding of modern AI frameworks and architectures.

This role requires a strong analytical mindset, excellent problem-solving capabilities, and the ability to evaluate and recommend the most effective approaches, models, and frameworks for diverse business use cases.

Key Responsibilities

• Design, develop, fine-tune, and deploy LLM-powered applications and solutions.

• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases.

• Implement parameter-efficient fine-tuning techniques such as LoRA and QLoRA.

• Work with frameworks such as LangChain, LangGraph, and Hugging Face to develop scalable AI applications.

• Train, fine-tune, evaluate, and optimize foundation models and domain-specific LLMs.

• Develop and maintain model deployment pipelines and production-grade AI systems.

• Analyze business requirements and recommend appropriate AI/ML architectures and frameworks.

• Collaborate with cross-functional teams to design scalable and efficient AI solutions.

• Contribute to system design discussions and provide high-level architectural recommendations.

Required Skills

• Strong experience with Large Language Models (LLMs) and Generative AI.

• Hands-on expertise in LoRA, QLoRA, and LLM fine-tuning techniques.

• Experience building Retrieval-Augmented Generation (RAG) applications.

• Proficiency in LangChain, LangGraph, and Hugging Face ecosystem.

• Experience with LLM training, evaluation, and optimization.

• Strong programming skills in Python and/or Java.

• Experience with model deployment, inference optimization, and productionization.

• Understanding of vector databases, embeddings, and semantic search concepts.

• Strong problem-solving, analytical, and logical reasoning skills.

• Good understanding of system design, scalability, and distributed architectures.

• Ability to evaluate multiple technical approaches and select optimal solutions based on business requirements.

Preferred Qualifications

• Experience with cloud platforms such as AWS, Azure, or GCP.

• Knowledge of MLOps, CI/CD pipelines, and containerization technologies.

• Familiarity with AI observability, monitoring, and model performance optimization.

• Experience building enterprise-grade GenAI applications.