Remote - Senior Generative AI Engineer

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Job description

Title: Senior Generative AI EngineerLocation: Remote (Prefer profiles from PST)Duration: Long TermJob 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.

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