Job Overview

We are seeking a Junior LLM Engineer to join our dynamic team at Huemn in Hyderabad. This full-time position requires 1 to 3 years of work experience. The ideal candidate will have a strong background in natural language processing and large language models, crucial for advancing our AI-powered tools. You will collaborate with cross-functional teams to enhance our innovative studio management technology, making a significant impact on the photography industry.

Qualifications and Skills

• Proficiency in natural language processing with a focus on implementing text and language algorithms.
• Experience with large language models, understanding their applications and limitations. (Mandatory skill)
• Knowledge of retrieval-augmented generation to improve the effectiveness and accuracy of AI outputs. (Mandatory skill)
• Strong programming skills in Python for developing scalable machine learning models.
• Familiarity with Hugging Face tools to leverage pre-trained models effectively for various NLP tasks.
• Understanding of TensorFlow for creating and training sophisticated neural networks on large datasets.
• Capable of working with knowledge graphs to enhance data interoperability and reasoning capabilities.
• Demonstrated ability to collaborate in a fast-paced environment and integrate new technologies into existing solutions.

Roles and Responsibilities

• Design and implement NLP solutions powered by state-of-the-art LLMs to enhance our tech tool suite.
• Collaborate with product and design teams to integrate AI features into existing photography management systems.
• Use RAG techniques to optimize the retrieval and generation capabilities of our AI models.
• Maintain and improve the existing AI infrastructure for optimal performance and scalability.
• Conduct research to stay updated with the latest advancements in AI and NLP technologies.
• Translate complex business requirements into technical solutions using knowledge graphs and data modeling.
• Participate in code reviews and provide constructive feedback to peers to maintain code quality.
• Contribute to a collaborative team environment, fostering a culture of continuous improvement and innovation.