Description

You will implement, fine-tune, and optimize Generative AI models, focusing on LLMs, prompt engineering, and RAG architectures.

This role is on-site.

Responsibilities

• Implement, fine-tune, and optimize Generative AI models using PyTorch, TensorFlow, or Keras.
• Develop LLM-based features, prompt engineering strategies, and AI automation workflows.
• Deploy and monitor AI/ML models in production, ensuring MLOps practices and containerization with Docker.
• Perform data preprocessing, feature engineering, and support API development for AI applications.
• Participate in code reviews, testing, documentation, and quality assurance alongside data science and engineering teams.

Required Skills

• 5+ years of experience in AI/ML development with proven delivery in agile environments.
• Strong proficiency in Python for AI/ML development, scripting, and data preprocessing.
• Hands-on experience with machine learning frameworks: PyTorch, TensorFlow, or Keras.
• Familiarity with LLMs, prompt engineering, and fine-tuning techniques (LoRA, QLoRA).
• Exposure to RAG (Retrieval-Augmented Generation) and hybrid search methodologies.
• Understanding of AI model deployment, MLOps practices, and Docker containerization.
• Proficiency in Git and version control best practices.

Preferred Skills

• Experience with Generative AI libraries: LangChain, Hugging Face, or LlamaIndex.
• Exposure to cloud-based AI/ML platforms (AWS, GCP, or Azure).

Key Skills

Education

Bachelor's or Master's degrees