Description

You will architect, fine-tune, and deploy Large Language Models (LLMs) and Generative AI techniques to enhance business applications.

This role is on-site.

Responsibilities

• Architect and deploy LLMs using RAG and PEFT/SFT techniques.
• Build scalable ML pipelines and GPU-based inference systems in AWS, GCP, or Azure.
• Implement prompt engineering and adversarial testing for safe, efficient model outputs.
• Define project scope, timelines, and success metrics while guiding offshore teams.

Required Skills

• 10+ years of experience as an ML Engineer, including 1-2 years in Generative AI or NLP.
• Strong proficiency in Python and IDEs like Cursor or AWS Kiro.
• Hands-on experience with LLMs (GPT-4, Llama), RAG, LangChain, and Vector Databases.
• Experience with MLOps/LLMOps using Docker, Kubernetes, and CI/CD tools.
• Deep knowledge of AWS services: S3, Lambda, Glue, SageMaker, and Bedrock.
• Experience working with PyTorch or TensorFlow.

Preferred Skills

• Ability to present AI methodologies and technical trade-offs to non-technical stakeholders.

Key Skills

Education

Any Gradute