Description

You will lead the development and deployment of generative AI systems, focusing on model fine-tuning, RAG architecture, and scalable infrastructure.

This role is hybrid.

Responsibilities

• Design and implement Retrieval-Augmented Generation (RAG) architectures, integrating diverse data sources and optimizing query processing.
• Develop and fine-tune large language models and image generation models, applying quantization, pruning, and knowledge distillation for optimization.
• Build scalable AI systems, including APIs, microservices, and data pipelines, collaborating with MLOps for production deployment.
• Provide technical guidance on generative AI strategies and mentor junior engineers to ensure adherence to best practices.
• Conduct experiments to improve model performance and stay current with AI research advancements.

Required Skills

• 7+ years of overall experience in AI/ML, with specific focus on generative AI and RAG architectures.
• Strong programming proficiency in Python.
• Hands-on experience with deep learning frameworks such as TensorFlow and PyTorch.
• Practical experience with GenAI technologies including OpenAI, Anthropic, or Llama.
• Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
• Demonstrable skills in Natural Language Processing (NLP) and computer vision.
• Bachelor's degree in Computer Science, Computer Engineering, or a related field.

Preferred Skills

• Experience building and managing production-grade AI microservices.
• Proven track record of mentoring engineering teams and driving technical strategy.

Key Skills

Education

Any Gradute