Satya Pattnaik
Senior Machine Learning Engineer at Apple
Hyderabad, Telangana, India
Summary
🤩
Rockstar🎓
Top SchoolSatya Pattnaik is a Senior Machine Learning Engineer with eight years of experience building and productionizing ML and deep learning systems across enterprise and cloud platforms. He has delivered NLP and MLOps solutions at Microsoft and led generative AI and LLM training and inference optimization work at Splunk, and now applies that expertise at Apple. His work spans transformers, distillation/quantization, multi-node GPU training (FSDP/DeepSpeed), and deployment on Azure and edge/server environments. An active open-source contributor, he enhanced PyCaret’s time-series plotting suite—adding decomposition, prediction-intervals, and diagnostic visuals—that improved time-series analysis for a widely used low-code ML library. Satya combines a solid academic foundation from BITS Pilani and advanced nanodegrees in deep and reinforcement learning with hands-on experience in causal inference and explainable AI. He’s known for bridging research-grade methods and pragmatic engineering to move models from prototype to reliable production services.
8 years of coding experience
7 years of employment as a software developer
BITS Pilani, Birla Institute of Technology and ScienceBachelor's Of Technology Computer Science, Bachelor's Of Technology Computer Science at Odisha University of Technology and ResearchAdvance Machine Learning Nanodegree Deep Learning and Reinforcement Learning, Advance Machine Learning Nanodegree Deep Learning and Reinforcement Learning at Udacity
Stackoverflow
21reputation
5kreached
1answer
0questions
Github Skills (12)
pandas10
machine-learning10
time-series10
python10
data-science10
plotly10
anomaly-detection6
pycaret6
scikit-learn6
regression5
classification4
clustering4
Programming languages (3)
Github contributions (5)
pycaret/pycaret
Aug 2021 - Dec 2021
An open-source, low-code machine learning library in Python
Role in this project:
Data Scientist
Data ScientistContributions:1 review, 9 commits, 5 PRs in 3 months
Contributions summary:Satya contributed significantly to the time series plotting utilities within the Pycaret library. Their work involved implementing various time series plots, including original series plots, train-test and cross-validation split visualizations, autocorrelation and partial autocorrelation plots, predictions, and diagnostic plots. The user also enhanced the plotting functions by incorporating options for prediction interval visualization, and added a decomposition plot. These contributions expand the time series analysis capabilities of Pycaret.
pythonpycarettime-seriesclassificationdata-science
satya-pattnaik/sktime
Mar 2021 - Jan 2022
A unified framework for machine learning with time series
Contributions:19 commits, 1 PR, 31 pushes in 10 months
deep-learningtime-seriesmachine-learning
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