Chinmay Singhal
New York, New York, United States
Summary
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SeniorChinmay Singhal is a Machine Learning Engineer based in New York with a decade of experience building and shipping production AI systems, currently focused on LLMs and scalable inference at Adobe. He has a strong full-stack background—designing cloud-native ML infrastructure on GCP/AWS with Kubernetes, deploying RAG pipelines, fine-tuning transformers, and integrating models with FastAPI/GraphQL frontends. At MD.ai he led LLM feature roadmaps and helped reduce radiology report completion time by 30% through tailored fine-tuning and evaluation workflows that drove enterprise adoption. He pairs rigorous academic training (MS in Data Science, NYU) with hands-on research in medical imaging and computational biology, and is comfortable bridging product requirements to reliable, performant AI services. Colleagues describe him as product-minded and execution-oriented, able to move models from research prototypes into revenue-generating deployments.
10 years of coding experience
Github Skills (15)
jupyter-notebook10
pytorch10
deep-learning9
testing8
lilypond8
python7
inference6
imaging5
capstone5
machine-learning5
segmentation4
wikipedia3
detector2
object-detection1
computer-vision1
Programming languages (3)
Github contributions (5)
mdai/model-deploy
Sep 2020 - Jan 2023
Model deployment for training/testing/inference on MD.ai
Contributions:2 reviews, 49 commits, 25 PRs in 2 years 3 months
inferencetesting
chinmaySinghal/chinmaySinghal
Dec 2020 - Jul 2023
Contributions:4 pushes, 1 branch in 2 years 7 months
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