Key Responsibilities

• Develop AI models using the latest advancements in LLMs and ensure their seamless integration into application frameworks.
• Optimize existing AI systems and models for improved efficiency and accuracy.
• Collaborate closely with data engineers and architects to implement effective data strategies for model training and evaluation.
• Stay current with AI research by attending conferences and workshops, bringing innovative ideas back to the team.
• Conduct rigorous testing and validation of AI models to ensure they meet quality standards.
• Write clean, manageable code and maintain proper documentation for all implemented AI systems.
• Participate in peer code reviews and contribute to team knowledge by providing expertise on coding standards and best practices.

Requirements & Skills

• Deep technical expertise in AI and machine learning, particularly in building and deploying large language models and transformers.
• Experience with RAG pipelines, vector embedding, and tokenization techniques, crucial for developing sophisticated AI systems.
• Strong knowledge of in-context learning, fine-tuning, zero-shot learning, few-shot learning, and prompting techniques.
• Proficiency in programming languages like Python, and experience with ML frameworks such as TensorFlow, PyTorch, and libraries from Hugging Face.
• Experience with cloud services (AWS, Azure, Google Cloud) and on-premises deployments, focusing on scalability and security of AI deployments.
• Ability to work collaboratively in a fast-paced, team-oriented environment

Educational Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, or related technical fields.