Description

You will architect, fine-tune, and deploy Large Language Models and Generative AI techniques to improve business applications. You will build scalable ML pipelines and GPU-based inference systems in cloud environments.

Responsibilities

• Architect and deploy LLMs using RAG, PEFT/SFT, and prompt engineering strategies.
• Build and maintain high-performance, scalable ML pipelines and GPU-based inference systems.
• Define project scope, timelines, and success metrics while guiding offshore technical teams.
• Implement adversarial testing and model optimization to ensure safe, high-quality outputs.
• Translate business requirements into technical specifications and communicate trade-offs to stakeholders.

Required Skills

• 10+ years of experience as an ML Engineer.
• 1-2 years dedicated to Generative AI or NLP projects.
• Strong proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
• Hands-on experience with LLMs (GPT-4, Llama), RAG architectures, LangChain, and Vector Databases.
• Proficiency in AWS (SageMaker, Bedrock, S3, Lambda, Glue) or GCP.
• Familiarity with Docker, Kubernetes, and CI/CD tools for ML.
• Experience using IDEs like Cursor/AWS Kiro and GitHub Copilot.
• Knowledge of Knowledge graphs and Agentic AI.

Preferred Skills

• Bachelor's degree in Computer Science or related field.
• Experience managing and coordinating with offshore technical teams.

Key Skills

Education

Bachelor's degree