As a Co-Founder & AIML Engineer at Pathixo Pvt. Ltd., you occupy a dual role that blends strategic leadership with deep technical execution. You are responsible for steering the company’s vision of delivering AI-powered and AI-assisted solutions that transform legacy workflows into high-efficiency, automation-ready systems. On the engineering side, you lead the architectural design and development of proprietary AI models, ensuring that every product—from initial MVP to full-scale deployment—leverages cutting-edge automation to solve real-world business bottlenecks. Your work bridges the gap between entrepreneurial strategy and technical feasibility, driving the innovation that defines Pathixo's market position.

At Outlier, the Data Scientist role is centered on the fine-tuning and alignment of next-generation Large Language Models (LLMs) to ensure they are helpful, honest, and harmless. The core work involves executing Supervised Fine-Tuning (SFT) by curating high-quality datasets to teach models specific behaviors and complex instruction-following capabilities. Additionally, you will play a critical role in Reinforcement Learning from Human Feedback (RLHF), where you evaluate model outputs, rank responses, and implement reward models to bridge the gap between raw statistical prediction and nuanced human intent. This position requires a deep understanding of model alignment cycles and a commitment to refining AI performance through rigorous iterative testing and data-driven optimization.

As an LLM Trainer at Outlier, you act as the critical human link in the evolutionary chain of advanced AI models. Your primary focus is on Reinforcement Learning from Human Feedback (RLHF) and Supervised Fine-Tuning (SFT), where you generate and evaluate high-quality data to teach Large Language Models (LLMs) logic, nuance, and safety. This involves crafting complex prompts, performing adversarial testing (red-teaming) to identify model weaknesses, and meticulously ranking model responses based on accuracy, tone, and adherence to specific instructions. By providing the "gold standard" data that models use to learn, you directly influence the reasoning capabilities and conversational intelligence of next-generation AI systems.

Working as a Remote AI Intern under the Microsoft and AICTE initiative, you serve as a bridge between foundational theory and enterprise-level cloud deployment. Your primary focus is on mastering the Azure AI ecosystem to build, train, and deploy scalable machine learning solutions. This involves hands-on experience within Azure AI Foundry and Azure Machine Learning Studio, where you manage the end-to-end ML lifecycle—from data ingestion and automated model training (AutoML) to deploying real-time inference endpoints. Beyond core ML, you leverage Databricks for big data processing and advanced analytics, ensuring that models are powered by clean, high-performance data pipelines. This role emphasizes the practical application of Deep Learning and Generative AI within a secure, cloud-native environment, preparing you to solve complex, real-world problems using industry-standard Microsoft technologies.