Job Description :
Title: Senior Generative AI Engineer
Location: Remote (Prefer profiles from PST)
Duration: Long Term
Job Experience Requirements:
" 10+ years Proficiency in Python and experience with Langchain, pyspark, PyTorch, Tensorflow, Streamlit and other relevant tools
" Prompt Engineering and AI Chatbot Acumen: Developing sophisticated AI chatbot solutions, including QA/chatbots, translation, and search/summarization functionalities.
" 5+ years of experience in GenAI Foundation Models and Vector DB: Leveraging foundational AI models and vector database technologies (multi vector) for advanced AI capabilities.
" 5+ years of experience in RAG (Retrieval-Augmented Generation) and Model Fine Tuning: Employing RAG techniques for enhanced AI responses and fine-tuning AI models for optimal performance.
" Use of Orchestration Tools: Utilizing advanced tools like Semantic Kerner, Langchain, and others for efficient AI model management.
" Expertise in either OpenAI or Google Vertex and/or other models from Hugging face for implementing advanced language models.
" Managing high availability and efficient deployment of cloud-native applications
" Experience with hosting LLMs on-premises.
" Experience with GitOps principles and tools, such as Git, Tekton, Flux, or ArgoCD, for managing infrastructure and application deployments.
" Strong problem-solving skills and the ability to work in a collaborative and fast-paced environment.
" 5+ years of experience in Automated Artificial Intelligence Tools
" 5+ years of experience in Machine Learning / AI
" 5+ years of experience in AWS, Azure, and other Cloud Platforms.
" 5+ years of experience in Docker and Kubernetes
" Bachelor s or master s degree in computer science, AI, or a related field
Job Responsibilities:
" This role is crucial in achieving the best RAG results on client data and contributing to the broader AI and machine learning community.
" Collaborate with cross-functional teams to understand business requirements and design AI solutions based on language models.
" Develop, train, and optimize language models using PyTorch, Tensorflow, and other relevant frameworks.
" Utilize expertise in either OpenAI or Google Vertex to implement state-of-the-art language models.
" Responsible for End-to-End RAG Solution Design and Development
" Lead the experimentation of different chunking and retrieval methods to enhance the efficiency and effectiveness of RAG systems.
" Developing, training, fine-tuning LLMs for RAG
" Conduct thorough evaluations of model and application performance.
" This entails a deep dive into model accuracy, bias identification, and the formulation of strategies for ongoing enhancement.
" Analytical skills that drive continuous improvements and set new benchmarks for excellence.
" Engage with customers from various sectors to facilitate the successful adoption of Unstructured APIs
" Bridge the gap between cutting-edge AI technology and industry-specific applications, ensuring clients achieve their strategic objectives.
" Collaborate with data scientists, software engineers, and other stakeholders to integrate AI solutions into enterprise applications.
" Proven experience in developing and deploying language models, with a focus on LLMs.