LLM Development Lead

Job Description:

Responsibilities:

• Develop and extend digital products and creative applications, leveraging LLM technologies at their core.
• Lead a product development and product operations team to further develop, enhance and extend existing digital products built on top of LLMs
• Lead client onboarding, client rollout, and client adoption efforts, maximizing use of the product across multiple clients
• Lead enhancements and extensions for client specific capabilities and requests
• Successful leadership and delivery of projects involving Cloud Gen-AI Platforms and Cloud AI Services, Data Pre-processing, Cloud AI PaaS Solutions, LLMs
• Ability to work with Base Foundation LLM Models, Fine Tuned LLM models, working with a variety of different LLMs and LLM APIs.
• Conceptualize, Design, build and develop experiences and solutions which demonstrate the minimum required functionality within tight timelines.
• Collaborate with creative technology leaders and cross-functional teams to test feasibility of new ideas, help refine and validate client requirements and translate them into working prototypes, and from thereon to scalable Gen-AI solutions.
• Research and explore emerging trends and techniques in the field of generative AI and LLMs to stay at the forefront of innovation.
• Research and explore new products, platforms, and frameworks in the field of generative AI on an ongoing basis and stay on top of this very dynamic, evolving field
• Design and optimize Gen-AI Apps for efficient data processing and model leverage.
• Implement LLMOps processes, and the ability to manage Gen-AI apps and models across the lifecycle from prompt management to results evaluation. 
• Evaluate and fine-tune models to ensure high performance and accuracy.
• Collaborate with engineers to develop and integrate AI solutions into existing systems.
• Stay up-to-date with the latest advancements in the field of Gen-AI and contribute to the company's technical knowledge base.

Must-Have:

• Strong Expertise in Python development, and the Python Dev ecosystem, including various frameworks/libraries for front-end and back-end Python dev, data processing, API integration, and AI/ML solution development.
• Minimum 2 years hands-on experience in working with Large Language Models
• Hands-on Experience with building production solutions using a variety of different.
• Experience with multiple LLMs and models - including Azure OpenAI GPT model family primarily, but also Google Gemini, Anthropic Claude, etc.
• Deep Experience and Expertise in Cloud Gen-AI platforms, services, and APIs, primarily Azure OpenAI.
• Solid Hands-on, and Deep Experience working with RAG pipelines and Enterprise technologies and solutions / frameworks - including LangChain, Llama Index, etc.
• Solid Hands-on Experience with developing end-to-end RAG Pipelines.
• Solid Hands-on Experience with AI and LLM Workflows
• Experience with LLM model registries (Hugging Face), LLM APIs, embedding models, etc.
• Experience with vector databases (Azure AI Search, AWS Kendra, FAISS, Milvus etc.).
• Experience with LLM evaluation frameworks such as Ragas, and their use to evaluate / improve LLM model outputs
• Experience in data preprocessing, and post-processing model / results evaluation.
• Hands-on Experience with API Integration and orchestration across multiple platforms
• Good Experience with Workflow Builders and Low-Code Workflow Builder tools such as Azure Logic Apps, or n8n (Nodemation)
• Good Experience with Serverless Cloud Applications, including Cloud / Serverless Functions with Azure
• Good Experience with Automation Workflows and building Automation solutions to facilitate rapid onboarding for digital products
• Ability to lead design and development teams, for Full-Stack Gen-AI Apps and Products/Solutions, built on LLMs and Diffusion models.
• Ability to lead design and development for Creative Experiences and Campaigns, built on LLMs and Diffusion models.

Nice-to-Have Skills (not essential, but useful) :

• Good understanding of Transformer Models and how they work.
• Hands-on Experience with Fine-Tuning LLM models at scale.
• Good Experience with Agent-driven Gen-AI architectures and solutions, and working with AI Agents.
• Some experience with Single-Agent and Multi-Agent Orchestration solutions
• Hands-on Experience with Diffusion Models and AI. Art models including SDXL, DALL-E 3, Adobe Firefly, Midjourney, is highly desirable.
• Hands-on Experience with Image Processing and Creative Automation at scale, using AI models.
• Hands-on experience with image and media transformation and adaptation at scale, using AI Art and Diffusion models.
• Hands-on Experience with dynamic creative use cases, using AI Art and Diffusion Models.
• Hands-on Experience with Fine-Tuning Diffusion models and Fine-tuning techniques such as LoRA for AI Art models as well.
• Hands-on Experience with AI Speech models and services, including Text-to-Speech and Speech-to-Text.
• Good Background and Foundation with Machine Learning solutions and algorithms
  Experience with designing, developing, and deploying production-grade machine learning solutions.
• Experience with Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
• Experience with custom ML model development and deployment
• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras. 
• Strong knowledge of machine learning algorithms and their practical applications.
• Experience with Cloud ML Platforms such as Azure ML Service, AWS Sage maker, and NVidia AI Foundry.
• Hands-on Experience with Video Generation models.
• Hands-on Experience with 3D Generation Models.

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