Jovian Jaison
Production Engineer at Meta
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJovian Jaison is a Production Engineer based in San Jose with eight years of experience building performant, reliable systems for AI and web applications. He combines production-focused engineering at Meta with prior work optimizing backend performance and CI/CD at Persistent Systems, where he cut response times and improved QA productivity. Jovian contributes to high-impact open source—making targeted performance and debugging improvements to PyTorch’s _dynamo module—and has implemented core data-structure algorithms across multiple languages. He has hands-on experience with LLMs and generative AI from an internship, research exposure at SJSU’s Interconnect Lab, and a strong foundation from an MS in Computer Science. Jovian’s practical blend of database tuning, backend refactoring, and ML infra work makes him adept at squeezing latency and cost out of production AI pipelines.
8 years of coding experience
3 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at San José State UniversityBachelor of Engineering - BE Computer Engineering, Bachelor of Engineering - BE Computer Engineering at Savitribai Phule Pune University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (22)
algorithms10
pytorch10
c-language10
selection-sort10
python10
circular-queue10
machine-learning10
c1110
data-structure10
aws-dynamodb10
c1710
amazon-dynamodb10
deeplearning-ai10
deep-learning10
dynamodb10
Programming languages (4)
Github contributions (5)
pytorch/pytorch
Jun 2024 - Mar 2025
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
ML Engineer
ML EngineerContributions:16 reviews, 24 PRs, 1 push in 8 months
Contributions summary:Jovian primarily contributed to the PyTorch library by modifying and enhancing the `_dynamo` module, likely focusing on performance and debugging capabilities for the dynamic compilation functionality. These modifications include adding logging for various configuration parameters related to compilation and improving the tracking of CUDA and Triton versions. Their work appears to involve optimizing the integration of these components within the PyTorch ecosystem. They also added testing regarding SparseAdam state_dicts.
pythongpu-accelerationdeep-learninggpunumpy
sukritishah15/DS-Algo-Point
Oct 2020 - Oct 2020
This repository contains codes for various data structures and algorithms in C, C++, Java, Python, C#, Go, JavaScript, PHP, Kotlin and Scala
Role in this project:Back-end Developer
Back-end DeveloperContributions:11 commits, 4 PRs, 6 comments in 3 days
Contributions summary:Jovian contributed implementations of various data structures and algorithms, including circular queues, selection sort, and preorder tree traversal. They wrote code in C and C++ and provided example inputs and outputs along with comments. Their work focused on demonstrating fundamental concepts in data structures and algorithms within a multi-language repository.
cpppythonleetcodejavascriptphp
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