Job Openings

Responsibilities:

• Utilize advanced LLMs such as GPT-3.5 Turbo, GPT-4, and Open LLM frameworks to build AI models for various applications.
• Data Collection & Preprocessing: Collect, preprocess, and analyze large volumes of structured and unstructured data from diverse sources.
• ML Pipeline Development: Design and maintain scalable machine learning pipelines for training, evaluation, and deployment of AI models.
• Proficiency in LangChain and LLMs: Perform tasks such as summarization, classification, Named Entity Recognition (NER), and question answering using LangChain and other Open LLM frameworks.
• Generative AI Techniques: Work with prompt engineering, vector databases, and LLMs like OpenAI, LlamaIndex, Azure OpenAI, and open-source LLMs to deliver solutions.
• GenAI & RAG Expertise: Apply Generative AI technologies, including RAG architecture, fine- tuning techniques, and inferencing frameworks.
• Continuous Learning: Stay updated on the latest advancements in AI and ML and integrate them into the projects to improve outcomes.
• Model Testing & Validation: Conduct thorough testing and validation of machine learning models to ensure their reliability, scalability, and robustness.
• Documentation & Collaboration: Document code, algorithms, and workflows to facilitate team collaboration and knowledge sharing.
• Conduct thorough testing and validation of machine learning models to ensure reliability, robustness, and scalability.
• Document code, algorithms, and processes to facilitate knowledge sharing and collaboration within the team.
• Participate in brainstorming sessions and contribute innovative ideas to enhance the performance and functionality of AI/ML applications.
• Support data preprocessing, feature engineering, and data visualization tasks to prepare datasets for model training and evaluation.
• Learn and apply best practices in AI/ML development, including model selection, hyperparameter tuning, and model evaluation techniques.