Professional Overview
AI engineer building things that work outside the lab multi-agent pipelines, LLM fine-tuning, RAG, and real-time voice AI. Currently researching Hinglish speech recognition, a 600M+ speaker gap with no good open-source solution. I ship fast and care about production, not demos.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Designed modular audio generation pipeline integrating TTS with sound design
- Built scalable architecture reducing manual content creation workflows
Key Achievements / KPIs
- Delivered reusable pipeline system adopted into production workflows
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Designed modular audio generation pipeline integrating TTS with sound design
- Built scalable architecture reducing manual content creation workflows
Key Achievements / KPIs
- Delivered reusable pipeline system adopted into production workflows
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
