Responsibilities
:
Generative AI Application Development
• Develop and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic AI Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs).
• Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.
Model Development and Deployment
• Design and develop machine learning models and algorithms to address business challenges and improve product features.
• Deploy machine learning models in production environments to ensure scalability and efficiency.
• Optimize and refine models based on performance metrics and feedback.
Data Management
• Collect, clean, and preprocess data from various sources to create robust datasets for training and evaluation.
• Implement data augmentation and feature engineering techniques to enhance model performance.
• Maintain and manage data pipelines to ensure seamless data flow and integration.
Python API Development
• Develop scalable APIs in python (fastApi, Apache, Gunicorn, Uvicorn) for model inferencing
Research and Innovation
• Stay updated with the latest trends and advancements in AI and machine learning technologies.
• Conduct research to explore new methodologies and techniques that can be applied to current and future projects.
• Collaborate with cross-functional teams to drive innovation and implement cutting-edge solutions.
Collaboration and Communication
• Work closely with software engineers, data scientists, and product managers to align AI/ML initiatives with business goals.
• Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner.
• Provide mentorship and guidance to junior team members and contribute to the upskilling of the team.s.