Description

You will build and deploy AI/ML applications leveraging GenAI and LLMs within an established architectural framework.

This role is on-site.

Responsibilities

• Execute end-to-end implementation of AI/ML solutions using GenAI and LLMs.
• Translate existing architectural designs into production-ready systems.
• Act as a Senior Developer for end-to-end implementation of GenAI/LLM solutions using existing PoCs and AI foundation models.
• Implement and manage MLOps pipelines using tools like MLflow, AWS SageMaker, and AWS Bedrock.
• Collaborate with Product Owners, AWS, and LLM vendors to build internal AI applications.

Required Skills

• 10+ years of hands-on experience in AI/ML engineering, including MLOps and production deployments.
• Expertise in Python, TensorFlow, Scikit-learn, NumPy, and PyTorch.
• Proficiency in AWS ML services, specifically SageMaker, Lambda, and S3.
• Practical experience with GenAI, LLMs, and prompt engineering.
• Solid understanding of AI/ML architectural concepts.
• Strong experience building and deploying machine learning models in production.
• Familiarity with GenAI, LLMs, AWS, MLflow, AWS SageMaker, and AWS Bedrock.

Preferred Skills

• Experience working with established architectural frameworks for AI solutions.

Key Skills

Education

Any Graduate