Generative AI Architect - NLP/LLM

Responsibilities :

- Design and implement advanced solutions utilizing Large Language Models (LLMs).

- Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions.

- Conduct research and stay informed about the latest generative AI and LLMs developments.

- Develop and maintain code libraries, tools, and frameworks to support generative AI development.

- Participate in code reviews and contribute to maintaining high code quality standards.

- Engage in the entire software development lifecycle, from design and testing to deployment

and maintenance.

- Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility.

- Possess strong analytical and problem-solving skills.

- Demonstrate excellent communication skills and the ability to work effectively in a team environment.

Primary Skills :

- Natural Language Processing (NLP) : Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation.

AND/OR

- Computer Vision and Audio : Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis.

Generative AI :

- Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, and Prompt engineering (COT, TOT, ReAct, agents).

- Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities.

- Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization.

- Cloud : Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred.

- Application Development : Proficiency in Python, Docker, FastAPI/Django/Flask, and Git.