Mukul Surajiwale
Staff ML Scientist @ Etsy | Ex-Staff MLE @ Shopify | Founding MLE @ HubSpot AI | CS @ Georgia Tech
- Role
- Staff Machine Learning Scientist at Etsy
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Mukul Surajiwale
Machine Learning Engineer with 9+ years of experience building and scaling end-to-end machine learning systems in Python, using tools like TensorFlow, PyTorch, Keras, Scikit-learn, and Hugging Face Transformers. I’ve led high-impact projects across the full machine learning lifecycle, from problem framing and data collection to model development, deployment, monitoring, and continuous improvement.I enjoy solving meaningful non-trivial problems at the intersection of research and application and love building things from zero to one with likeminded mission-driven people who care deeply about the societal impact of their work.Currently, I am working at Etsy as a Staff Machine Learning Scientist.Before Etsy, I worked at Writer, where I led the development of a next-generation multimodal, agentic, vision-based information retrieval system to enable accurate natural language QA.Before Writer, I was a Staff Machine Learning Engineer at Shopify, where I led applied research on LLMs and information retrieval for e-commerce.Before Shopify, I was a founding member of the Artificial Intelligence group at HubSpot, where I rose to become the most senior IC MLE and helped grow the team from 5 to XX+ members.My work covers the following- Training and deploying LLMs for multimodal information retrieval and QA- Building LLM fine-tuning, evaluation, and serving layers for HubSpot’s ML-Ops platform- Fine-tuning and serving LLM models for specific use case using SFT and DPO- Real-time streaming anomaly detection and forecasting on time series data- LLM-based topic detection in conversations- Bayesian Active Learning- Markov chains for user action prediction- Text classification, clustering, and similarity- Search: semantic retrieval, ranking, and performance monitoring- Contextual multi-armed bandits for adaptive A/B testing- Deep learning based recommender systems for lead scoring, video recommendations, and search result ranking- Abuse detection for email listsIn my free time, I enjoy reading, writing, sailing, and engaging with all things automotive.My superpowers are curiosity, integrity, and locally reducing entropy.
Experience
Staff Machine Learning Scientist
Sep 2025 — Present · New York, NY, US
Education
Rensselaer Polytechnic Institute
Bachelor of Science - BS, Computer Science, Minor in Business
Georgia Institute of Technology
Master of Science - MS, Computer Science, Concentration in Machine Learning
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