I seek roles building production ML/LLM systems in product-focused teams, with ownership of model design, deployment, and measurable user impact.
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@xtrawork
Senior AI engineer specializing in production ML, LLM systems, and recommender platforms.
I seek roles building production ML/LLM systems in product-focused teams, with ownership of model design, deployment, and measurable user impact.
I am a Senior AI Engineer with deep experience building production-grade ML systems, LLM pipelines, and recommender platforms for high-concurrency consumer products. I design modular multi-agent LLM architectures, deterministic evaluation frameworks, and scalable MLOps to deliver reliable, insight-driven applications.
At Info Edge I led ML for an Ed-Tech vertical, productionized neural learning-to-rank models, deployed RAG-based personalized chatbots, and built recommender systems that meaningfully increased CTR and conversions. I have improved model performance and user engagement through transformer-based solutions, localization (Hinglish) tools, and predictive modelling.
I also bring startup and research experience across healthcare imaging and adversarially robust vision, with a record of publications and hands-on MLOps using Docker, Kubernetes, MLflow, and in-house serving stacks to achieve high uptime and reduced latency.
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Work history, roles, and key accomplishments
Knit
Jun 2025 - Present (5 months)
Built a modular multi-agent LLM pipeline to automate research workflows from raw survey ingestion to insight-rich memos with tables, summaries, and visualizations; engineered a hierarchical Judge LLM framework to evaluate and ensure factual accuracy and qualitative consistency of AI-generated reports.
Led ML for the Shiksha ed-tech vertical, productionized transformer-based learning-to-rank and deployed RAG LLM chatbot, improving search NDCG/CTR and achieving >85% positive user feedback for the personalized counseling bot; delivered recommender systems that boosted CTRs by 25% and improved lead conversion 12x for study abroad.
Niramai
Feb 2020 - May 2020 (3 months)
Improved breast-cancer detection sensitivity from 90% to 92% using novel CNN variants for depth estimation and built core data pipelines and feature engineering that supported clinical-grade performance.
Bioretics
Nov 2018 - Jun 2019 (7 months)
Implemented an active learning framework for image segmentation using FCNs, achieving target performance with 53% labeled data and halving annotation costs.
Ecole Polytechnique
Jan 2019 - May 2019 (4 months)
Analyzed similarities between mouse auditory pathways and CRNN audio processing via convolutional filter visualization, producing novel research recognized with top university grade.
CNRS
May 2018 - Aug 2018 (3 months)
Developed methods to improve robustness of convolutional neural networks against adversarial attacks by infusing semantic knowledge, increasing robustness by 20% and leading to a conference publication.
Degrees, certifications, and relevant coursework
Post Graduate Programme in Machine Learning, Machine Learning
2019 - 2020
Completed the Post Graduate Programme in Machine Learning as a Plaksha Fellow from August 2019 to July 2020.
Bachelor of Technology, Computer Science Engineering
2015 - 2019
Earned a Bachelor of Technology in Computer Science Engineering from August 2015 to July 2019.
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