AnweshSatapathy 

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Summary

👤
Senior
Anwesh Satapathy is a Machine Learning Engineer with a decade of experience building production-grade ML and backend systems, currently optimizing inference at Snap in San Francisco. He has engineered end-to-end LLM solutions (RAG, LoRA/QLoRA, AWQ), scalable microservices, and real-time vLLM inference stacks that delivered multi-fold throughput improvements and sub-second latency gains. Previously at Dell he drove NLP pipelines, Kafka streaming, and resilient CI/CD that supported 10M+ device tracking and cut operational effort by 90%. Comfortable across distributed training (FSDP, DeepSpeed), large-scale data pipelines (Spark, Hive), and observability (Prometheus/Grafana), he combines research-caliber rigor (ASU MS, 4.0 GPA) with practical production reliability. Notably, he blends deep model tuning with backend engineering to squeeze latency and cost from inference—not just accuracy—making models cheaper and faster in real-world systems.
code10 years of coding experience
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Github Skills (18)

cycle10
kubernetes9
python9
cuda9
gpt8
inference8
amd8
artificial-intelligence8
pytorch8
tpu7
llm7
machine-learning7
deep-learning7
mlops7
transformer7

Programming languages (4)

JavaScriptHTMLJupyter NotebookPython

Github contributions (5)

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Contents covered in sessions of AI Saturdays (cycle 2) as well as relevant material for further study.
Contributions:86 commits, 78 pushes, 1 branch in 6 months
deep-learningmachine-learningcyclecontentsartificial-intelligence
Anwesh2/anwesh2.github.io

Feb 2018 - Feb 2018

Contributions:124 pushes, 1 branch in 2 days
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AnweshSatapathy