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).
• Implement prompt engineering, adversarial testing, and model optimization for quality and safety.
• Define project scope, timelines, and deliverables while coordinating with offshore technical teams.
• Translate business requirements into technical specifications when collaborating with product managers and data scientists.

Required Skills

• 10+ years of experience as an ML Engineer, with 1-2 years specifically in Generative AI or NLP.
• Strong proficiency in Python and IDEs such as Cursor or AWS Kiro.
• Hands-on experience with LLMs (e.g., GPT-4, Llama), RAG architectures, LangChain, and Vector Databases.
• Familiarity with Docker, Kubernetes, and CI/CD tools for ML operations.
• Experience with AWS services including S3, Lambda, Glue, AWS SageMaker, and AWS Bedrock.
• Proven ability to articulate complex technical concepts to non-technical stakeholders.
• Expertise in deep learning frameworks such as PyTorch or TensorFlow.

Key Skills

Education

Any Graduate