Siddhant Pradhan
Machine Learning Engineer at Meta
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolSiddhant Pradhan is a Machine Learning Engineer with eight years of experience building production-grade ML systems, currently focused on ads explainability and privacy at Meta. He previously co-developed a YAML-configurable MLOps platform at Stovell AI that scaled from one to 50+ models and contributed to a product generating $10M ARR, owning end-to-end model development and infrastructure. His research background from UMass Amherst spans reinforcement learning, probabilistic ML, and differential privacy, and he has published work on human-in-the-loop multi-agent RL and time-series/irregular-sampled sequence modeling. Comfortable across TensorFlow, PyTorch, GCP, Snowflake and Kubeflow, he blends academic rigor with hands-on engineering—an example being novel time-decay embeddings and practical pipelines that cut productionization time by over 72%. Based in the NYC area, he actively seeks open-source and research collaborations, bringing startup-scale ownership and research-driven innovation to large-product environments.
8 years of coding experience
4 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)Master's degree Computer Science, Master's degree Computer Science at University of Massachusetts Amherst
English, Marathi, Hindi
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
python7
shell7
q-learning6
reinforcement-learning5
deep-learning5
machine-learning5
gymnasium5
multi-agent4
agent3
deep-reinforcement-learning3
multi-agent-reinforcement-learning3
Programming languages (3)
Github contributions (5)
siddhant-pradhan/private-pgm
Nov 2020 - Mar 2021
An implementation of the tools described in the paper entitled "Graphical-model based estimation and inference for differential privacy"
Contributions:1 PR, 12 pushes, 1 branch in 3 months
model-basedprivacydifferential-privacyinferenceestimation
siddhant-pradhan/self_learning
Aug 2023 - Sep 2023
Contributions:2 pushes, 1 branch in 15 days
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