Gen AI Engineer

Company Description

Office Solution AI Labs, a global consulting and GEN AI powerhouse, specializes in Outsourced Product Development, Business Process Management, and Custom Application Development & Maintenance. We are an Authorized Microsoft Partner committed to delivering exceptional value to our clients through innovative data solutions. Leveraging cutting-edge technologies such as D3, React, and TypeScript, we create custom charts and Power BI visualizations to empower businesses with data-driven decision-making. With over 10 years of industry experience, we have successfully delivered numerous projects to clients across the United States, United Kingdom, Canada, Europe, and Dubai. OverviewWe're seeking a passionate and skilled Generative AI Engineer to join our innovative team. The ideal candidate will have a deep understanding of machine learning principles and hands-on experience in building and deploying generative AI models. This role will focus on developing applications that leverage Large Language Models (LLMs) and implementing the Retrieval-Augmented Generation (RAG) framework to create intelligent, context-aware, and factual AI solutions. You will be instrumental in pushing the boundaries of what our products can achieve, working on everything from ideation to production deployment.Roles & Responsibilities1 Model Development and Fine-Tuning: Design, train, and fine-tune generative AI models, with a specific focus on LLMs like GPT, Llama, and others. Optimize these models for performance, efficiency, and scalability.2 RAG System Implementation: Architect and build robust RAG pipelines. This involves designing and managing knowledge bases (vector databases), creating efficient data retrieval mechanisms, and integrating them with LLMs to provide contextually accurate and up-to-date responses.3 Prompt Engineering: Develop and refine advanced prompt engineering techniques to guide LLMs and RAG systems to produce high-quality, relevant, and consistent outputs.4 Data Management and Pipelines: Work with large, complex datasets for model training and retrieval. This includes data cleaning, preprocessing, and building automated data pipelines to ensure the integrity and currency of the knowledge base.5 Deployment & MLOps: Deploy and manage generative AI models and applications in production environments. Implement MLOps (Machine Learning Operations) practices for continuous integration/continuous deployment (CI/CD), monitoring, and maintenance of models.6 Collaboration and Research: Work closely with data scientists, product managers, and other engineering teams to define project requirements and deliver on business goals. Stay current with the latest advancements in generative AI and apply new research to our products.7 Ethical AI Practices: Ensure all AI solutions are developed with a strong emphasis onfairness, privacy, and transparency, mitigating risks of bias and ensuring responsible use.Required Qualifications & SkillsEducation: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.Experience:o Hands-on experience in building and deploying generative AI applications.o Proven experience with Large Language Models (LLMs) and their architectures (e.g., Transformers).o Direct experience implementing and optimizing Retrieval-Augmented Generation (RAG) systemsTechnical Skills:o Programming Languages: Expert proficiency in Python and its relevant libraries (e.g., PyTorch, TensorFlow, Hugging Face).o Machine Learning Frameworks: Strong knowledge of deep learning frameworks such as PyTorch or TensorFlow.o NLP: Solid understanding of Natural Language Processing (NLP) concepts and techniques.o Databases: Experience with vector databases (e.g., Pinecone, Weaviate, Milvus) and traditional databases.o Cloud Platforms: Familiarity with cloud services like AWS, GCP, or Azure, and containerization technologies like Docker and Kubernetes.Soft Skills:o Excellent problem-solving and analytical skills.o Strong communication and collaboration abilities.o A proactive, creative, and results-oriented mindset.Preferred Qualifications Experienced in working with both open-source LLMs (LLaMA, Phi, Qwen, etc.) and closed- source/commercial models (OpenAI GPT, Gemini, etc.) for Generative AI applications. Experience with other generative AI frameworks such as LangChain and LlamaIndex. Contributions to open-source projects related to AI. Experience in a production-focused MLOps environment.