Sayan Goswami
Machine Learning Engineer at Meta
Stony Stratford, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolSayan Goswami is a machine learning engineer with 11 years' experience building production-grade systems across Amazon Ads and Meta, blending software engineering, distributed systems, security, and ML. He has strong hands-on SRE/MLOps experience from roles at Sea AI Lab and contributed research-grade ML work in academia on quantum computing and reinforcement learning. At Amazon he progressed from SDE to SDE-II, and his open-source contributions include implementing NSGA-II multi-objective optimization in the notable mlpack/ensmallen C++ library. Comfortable moving between low-latency systems, orchestration, and optimization research, he has a track record of shipping resilient infrastructure and research prototypes without downtime. Based in the UK, he combines rigorous academic training from Universitat Pompeu Fabra and Jadavpur University with pragmatic production delivery.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering - BE Electronics and Telecommunication Engineering, Bachelor of Engineering - BE Electronics and Telecommunication Engineering at Jadavpur UniversityMaster of Science - MS Intelligent Interactive Systems, Master of Science - MS Intelligent Interactive Systems at Universitat Pompeu FabraHigh School Computer Science, High School Computer Science at Delhi Public School, Ruby Park
Spanish, Bengali, Hindi, English
Stackoverflow
1,530reputation
466kreached
50answers
3questions
ftp
top-5%
xampp
top-5%
Github Skills (20)
algorithm10
c-language10
optimizers10
machine-learning10
optimisation10
cprogramming-language10
optimization10
xampp9
ftp9
minimize9
minification9
filezilla6
android6
python6
caching6
Programming languages (20)
Github contributions (5)
mlpack/ensmallen
Dec 2019 - Aug 2020
A header-only C++ library for numerical optimization --
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:8 reviews, 141 commits, 10 PRs in 8 months
Contributions summary:Sayan primarily focused on extending the functionality of the `ensmallen` library by adding a multi-objective optimization algorithm, NSGA2. Their contributions involved implementing the NSGA2 optimizer, including core components like the FastNonDominatedSort, and related functionalities. They also updated the release script and test suites, adding tests for the newly implemented optimization features. The commits also included some refactoring and improvements of the code style.
optimization-methodsoptimization-algorithmsnumerical-optimizationheader-onlycplusplus
say4n/deepcosegmentation.pytorch
Jun 2018 - Sep 2018
Contributions:209 commits, 35 pushes, 1 branch in 3 months
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