Description

You will build, fine-tune, and deploy Generative AI and Large Language Model applications using Python and modern deep learning frameworks.

This role is on-site.

Responsibilities

• Develop and optimize models using PyTorch and TensorFlow, including fine-tuning and prompt engineering for LLMs.
• Implement RAG architectures and manage data pipelines with SQL, NoSQL, Pandas, and NumPy.
• Deploy and maintain ML solutions on cloud platforms (AWS/Azure/GCP) following MLOps best practices.
• Leverage Hugging Face, Scikit-learn, and Keras to solve complex engineering problems.
• Collaborate on system design, ensuring robust data handling and model performance.

Required Skills

• Expert-level proficiency in Python programming.
• Hands-on experience with PyTorch or TensorFlow deep learning frameworks.
• Strong background in Generative AI, LLMs, prompt engineering, and RAG techniques.
• Proficiency in SQL and NoSQL databases for data manipulation and retrieval.
• Experience with cloud platforms (AWS, Azure, or GCP) for deployment and scaling.
• Familiarity with libraries such as Scikit-learn, Keras, and Hugging Face.
• Knowledge of foundational mathematics and data preprocessing tools (Pandas, NumPy).
• Additional programming skills in R, C++, or Java are advantageous.

Preferred Skills

• Experience with Ollama or similar local LLM inference tools.
• Background in MLOps and CI/CD for machine learning workflows.
• Demonstrated ability to deploy production-grade AI systems.

Key Skills

Education

Any Graduate