I'm an AIML Platform Engineer with extensive experience in software engineering and large-scale ML training. I specialize in Python, cloud platforms (AWS, Google Cloud, Azure), and infrastructure-as-code tools (Terraform, Docker, Kubernetes), with a track record of deploying ML models using PyTorch, TensorFlow, and Hugging Face in production. I lead cross-functional teams in agile environments, design scalable AIML platforms focused on usability, reproducibility, and performance at scale, with a passion for building robust MLOps pipelines, CI/CD, and high-performance computing.

Sumanth Murthy

I'm an AIML Platform Engineer with extensive experience in software engineering and large-scale ML training. I specialize in Python, cloud platforms (AWS, Google Cloud, Azure), and infrastructure-as-code tools (Terraform, Docker, Kubernetes), with a track record of deploying ML models using PyTorch, TensorFlow, and Hugging Face in production. I lead cross-functional teams in agile environments, design scalable AIML platforms focused on usability, reproducibility, and performance at scale, with a passion for building robust MLOps pipelines, CI/CD, and high-performance computing.

Available to hire

I’m an AIML Platform Engineer with extensive experience in software engineering and large-scale ML training. I specialize in Python, cloud platforms (AWS, Google Cloud, Azure), and infrastructure-as-code tools (Terraform, Docker, Kubernetes), with a track record of deploying ML models using PyTorch, TensorFlow, and Hugging Face in production.

I lead cross-functional teams in agile environments, design scalable AIML platforms focused on usability, reproducibility, and performance at scale, with a passion for building robust MLOps pipelines, CI/CD, and high-performance computing.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert

Language

English
Fluent

Work Experience

Computer Vision Lead & ML Platform Architect at CYTED - Microsoft Research Collaboration
December 31, 2022 - September 8, 2025
Led platform development for large-scale ML training using PyTorch and TensorFlow; Implemented MLOps pipelines using MLFlow and Kubeflow for model deployment; Deployed distributed training achieving 94% AUROC using multi-GPU environments; Built production Python code with comprehensive testing and documentation toolchains; Integrated DataOps practices for processing thousands of medical images at scale; Participated in design reviews and PR reviews ensuring engineering best practices; Used Huggingface frameworks to build LLM-based chatbot for clinical use.

Education

MSc in Computer Science and Engineering at University of Toronto
January 11, 2030 - September 8, 2025
Master's degree (MSc) in Computer Science and Engineering at University of Toronto
January 11, 2030 - September 8, 2025

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Healthcare, Life Sciences, Professional Services, Education, Media & Entertainment