Mogith P N

Proficient in developing ML/AI frontend modules using Streamlit and Clarifai-Python SDK for tailored user-specific ML tasks, ensuring a rich, no-code user experience. Actively contributed to impactful open-source projects such as Langchain, Llamaindex, DSPy (Stanford), Unstructured.IO, and Embedchain by integrating the Clarifai platform, enhancing access to LLM, ML, and CV models, while leveraging the Clarifai app as a Vector database. Spearheaded ISV partner integrations with Databricks, leading Proof of Concepts (POCs) and developing the 'Clarifai-pyspark' SDK package, enabling seamless two-way data movement between Clarifai and Databricks, thus optimizing clients' AI journeys. Engaged in active research on prompt engineering, vector search and data processing to identify critical gaps in tech stacks for implementing RAG (Retrieval Augmented Generation) applications tailored for specific business cases. Contributed significantly to the development and enhancement of the Clarifai-Python SDK, focusing on extending its capabilities and integrating gRPC functions during active sprint cycles.

Streamlined the Deployment of monthly OS rollout for 3000+ servers hosted on AWS cloud across different environments and implemented cost optimization solutions. Seamlessly integrating with business stakeholders and cross-functional engineering teams to refine project deliverables and maintain high uptime of resources and services.

Optimized the cycle time for assembly processes using robust methods. led the other interns with a batch of 6 in the task of integrating production machines with Industry 4.0 compliance.

Python (Pandas, NumPy, Sci-Kit learn), SQL, MongoDB, Data Engineering, Data Visualization, Machine Learning, Feature engineering, and Natural language processing.