| Gen AI Full stack Developer in Tampa, FL/Dallas, TX, NJ Onsite at Tampa, Florida, USA |
| Email: [email protected] |
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http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=2226329&uid= Hi Hope you are doing well, We have the below requirement open. Please send me your candidates updated Resume to [email protected] Role: GenAI Fullstack Developer Location: Tampa, FL/Dallas, TX, NJ(Onsite) NOTE : Need Passport number and LinkedIn ID and please do mention Current Location and Visa of candidate while sending the As a GenAI Full-Stack Developer at client you will play a pivotal role in shaping the future of AI by designing, developing, deploying, and maintaining cutting-edge GenAI applications, specifically focusing on RAG applications. You will leverage your expertise in both front-end and back-end development, machine learning, and GenAI techniques to create a seamless user experience for our clients. Role and responsibilities Collaborate with data engineers, data scientists, and stakeholders to understand data requirements, problem statements, system integrations, and RAG application functionalities. Utilize, apply & enhance GenAI models using state-of-the-art techniques like transformers, GANs, VAEs, LLMs (including experience with various LLM architectures and capabilities), and vector representations for efficient data processing. Implement and optimize GenAI models for performance, scalability, and efficiency, considering factors like chunking strategies for large datasets and efficient memory management. Integrate GenAI models, including LLMs, into production pipelines, applications, existing analytical solutions, and RAG workflows, ensuring seamless data flow and information exchange. Develop user-facing interfaces (UIs) using modern front-end frameworks (e.g., React, Angular) to deliver an intuitive and interactive experience for RAG applications. Develop robust APIs (RESTful or GraphQL) using back-end frameworks (e.g., Django, Node.js) to facilitate communication between the front-end UI, GenAI models, and data sources. Utilize LangChain and similar tools (e.g., PromptChain) to facilitate efficient data retrieval, processing, and prompt engineering for LLM fine-tuning within RAG applications. Apply software engineering principles to develop secure, scalable, maintainable, and production-ready GenAI applications. Build and deploy GenAI applications on cloud platforms (AWS, Azure, or GCP), leveraging containerization technologies (Docker, Kubernetes) for efficient resource management. Integrate GenAI applications with other applications, tools, and analytical solutions (including dashboards and reporting tools) to create a cohesive user experience and workflow within the RAG ecosystem. Continuously evaluate and improve GenAI models, applications, and user interfaces based on data, feedback, user needs, and RAG application performance metrics. Stay up-to-date with the latest advancements in GenAI research, development, front-end and back-end development practices, integration tools, LLM architectures, and RAG functionalities. Document code, models, processes, UI/UX design choices, and RAG application design for future reference and knowledge sharing. Technical skills requirements The candidate must demonstrate proficiency in, Strong understanding of machine learning and deep learning concepts Proficiency in Python (libraries like TensorFlow, PyTorch) with experience in vector data manipulation libraries Experience with generative AI models (transformers, GANs, VAEs) and various LLM architectures Experience with front-end development frameworks (e.g., React, Angular) and UI/UX design principles Experience with back-end development frameworks (e.g., Django, Flask) and API development (RESTful or GraphQL) Experience with NLP techniques (text cleaning, pre-processing, text analysis) Experience with software engineering principles and best practices (object-oriented programming, design patterns, testing) Familiarity with cloud platforms (AWS, Azure, or GCP) Knowledge of containerization technologies (Docker, Kubernetes) Experience with data integration tools and techniques (a plus) Knowledge of chunking strategies for handling large datasets Experience working with RAG applications and their functionalities Experience in utilizing LangChain, LangGraph, and other agentic framework tools (e.g., AutoGen, Crew.ai) to facilitate efficient data retrieval, processing, prompt engineering, and multi-step reasoning within RAG applications. Experience building and deploying autonomous agents for specific tasks within the RAG ecosystem is highly desirable Experience with DevOps principles and tools for continuous integration and delivery (CI/CD) Experience with building and integrating with analytical dashboards and reporting tools Nice-to-have skills Experience working with RAG applications Experience with cloud-based data warehousing solutions (e.g., BigQuery, Redshift, Snowflake) Experience with cloud-based workflow orchestration tools (e.g., Airflow, Prefect) Familiarity with Kubernetes (K8S) is a welcome addition Google Cloud certification Unix or scripting Qualifications B.Tech., M.Tech. or MCA degree from a reputed university Thanks and Regards, Ramya Sri https://www.linkedin.com/in/ramya-sri-66152a23b/ Email: [email protected] -- Keywords: continuous integration continuous deployment artificial intelligence user interface user experience javascript information technology Florida Idaho New Jersey Texas Gen AI Full stack Developer in Tampa, FL/Dallas, TX, NJ Onsite [email protected] http://bit.ly/4ey8w48 https://jobs.nvoids.com/job_details.jsp?id=2226329&uid= |
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| 12:22 AM 05-Mar-25 |