Praateek Mahajan
Senior Software Engineer at NVIDIA
San Francisco, California, United States
Summary
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Rockstar🎓
Top SchoolPraateek Mahajan is a Senior Software Engineer with 10 years of experience building and scaling machine learning platforms and data workflows for internet-scale model training, currently accelerating foundational-model pipelines at NVIDIA. He previously architected ML infrastructure at Block and led platform work across multiple roles at Iterable and Square, blending production engineering with research-grade ML rigor. Praateek holds an MSE in Computer Science with a focus on machine learning from Johns Hopkins and has hands-on research experience in latent video representations and timeseries embeddings. An active open-source contributor, his meta-learning work on the popular learn2learn library (TaskGenerator, LabelEncoder, dataset sampling improvements) reflects a knack for clean data handling that benefits few-shot and meta-learning experiments. Based in San Francisco, he combines deep academic foundations with practical wins—reducing storage costs, revamping search, and shipping high-throughput data pipelines—making him adept at turning research into reliable production systems. He often sits at the intersection of ML research and engineering, favoring solutions that scale without sacrificing experimental flexibility.
10 years of coding experience
9 years of employment as a software developer
Johns Hopkins UniversityBachelor of Technology (BTech) Computer Science, Bachelor of Technology (BTech) Computer Science at Shaheed Sukhdev College Of Business StudiesPhysics Chemistry Maths and Computer Science, Physics Chemistry Maths and Computer Science at St. Columba's School
English, Hindi
Stackoverflow
11reputation
2kreached
0answers
2questions
Github Skills (10)
meta-learning10
pytorch10
machine-learning10
apache-spark6
databricks6
pyspark6
intel6
x86-166
microprocessors6
x866
Programming languages (7)
Github contributions (5)
learnables/learn2learn
Aug 2019 - Mar 2020
A PyTorch Library for Meta-learning Research
Role in this project:
ML Engineer
ML EngineerContributions:74 commits, 35 PRs, 68 pushes in 7 months
Contributions summary:Praateek primarily focused on implementing and refining a `TaskGenerator` class within a meta-learning research library. The contributions involve creating a dataset class, modifying the sample method to return a dataset, and implementing an `LabelEncoder` class. Further development included the ability to split the task generation into train/test splits and adapt the batch size. This work demonstrates a focus on data handling and task creation for meta-learning experiments.
pytorchmeta-learningmetalearningmeta-optimizationdeep-learning
praateekmahajan/machinelearningconcepts
Mar 2018 - Feb 2019
Contributions:16 commits, 15 pushes, 1 branch in 11 months
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