Description

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

Responsibilities

• Architect, fine-tune, and deploy LLMs and Generative AI techniques like RAG and PEFT/SFT.
• Build and maintain scalable ML pipelines and GPU-based inference systems in cloud environments (AWS/GCP/Azure).
• Translate business requirements into technical specifications by collaborating with product managers and data scientists.
• Implement prompt engineering and adversarial testing to ensure high-quality, efficient, and safe model outputs.
• Define project scope, timelines, and success metrics while guiding offshore technical 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 such as Cursor/AWS Kiro.
• Hands-on experience with LLMs (e.g., GPT-4, Llama), RAG, LangChain, and Vector Databases.
• Familiarity with MLOps and LLMOps using Docker, Kubernetes, and CI/CD tools.
• Experience with AWS services, specifically S3, Lambda, Glue, AWS SageMaker, and AWS Bedrock.
• Proven ability to present AI methodologies and technical trade-offs to non-technical stakeholders.
• Experience working with PyTorch or TensorFlow.
• Ability to troubleshoot complex issues independently in a fast-paced setting.

Key Skills

Education

Any Gradute