<aside> 👋 I build resource-optimized, interpretable ML models with my code. I have two years of experience as an ML engineer where I collaborated with multiple partner teams such as Business, Product Management, Strategy, and Business Management to deploy solutions into production.

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Contact

📧 [email protected]

🔗 linkedin.com/in/akashchaudhari

👾 https://github.com/akashchaudhari98

Experience

Graduate Research Assistant

University of Rochester, USA (May 2023 - Present)

• Developing a modeling framework for inducing combinatory categorial grammars from arbitrary behavioral data by integrating tree structures into transformer networks.

Machine learning Engineer

Hansa Cequity, Mumbai, India – (Aug 2021 - Aug 2022)

• Developed a ****reliable, robust, & scalable NLP pipeline for sequence labeling & sentiment analysis using RoBerta classifier, Pytorch, & Spacy pipelines, achieving an evaluation F1 score of 94.7%.
• Developed end-to-end ML pipeline to generate recording transcripts, and trained BERT models to identify the intent of call( 89.4% F1).
• Designed an Information Retrieval pipeline to identify entities and speakers in the unstructured transcripts, & run end-to-end analysis to measure various call center KPIs such as customer satisfaction, consumer complaints, and product opinion.
• Designed & deployed an architecture for a real-time recommendation and personalization system on GCP. Implemented active learning & designed a system to track daily model performance. automatic topi
• Designed and trained a semi-supervised multi-stage data2text model to generate textual reports from CSV files.
• Deployed a machine-learning pipeline of 12 models to train daily and run inference on 8 million data points.Implemented model and data versioning.
• Performed Exploratory Data analysis on Human Resources data( HR Analytics). Explored year-on-year and monthly trends and built an attrition prediction model using statistical machine-learning algorithms.

Machine learning Engineer