I'm Chandan Mohan, a Machine Learning Platform Engineer based in San Francisco. I design and operate end-to-end ML infrastructure and pipelines across AWS, GCP, and Kubernetes, focusing on reliability, scalability, and observability. I excel at data engineering, model deployment, and automating CI/CD processes using TensorFlow, MLflow, Terraform, and Docker. I collaborate with data scientists, engineers, and operations teams to deliver high-quality ML solutions with measurable impact. I enjoy bridging gaps between disciplines to accelerate delivery while maintaining governance and security. My track record includes reducing deployment time, improving model reliability, and delivering cost savings through automation and efficient workflows.

Chandan Mohan

I'm Chandan Mohan, a Machine Learning Platform Engineer based in San Francisco. I design and operate end-to-end ML infrastructure and pipelines across AWS, GCP, and Kubernetes, focusing on reliability, scalability, and observability. I excel at data engineering, model deployment, and automating CI/CD processes using TensorFlow, MLflow, Terraform, and Docker. I collaborate with data scientists, engineers, and operations teams to deliver high-quality ML solutions with measurable impact. I enjoy bridging gaps between disciplines to accelerate delivery while maintaining governance and security. My track record includes reducing deployment time, improving model reliability, and delivering cost savings through automation and efficient workflows.

Available to hire

I’m Chandan Mohan, a Machine Learning Platform Engineer based in San Francisco. I design and operate end-to-end ML infrastructure and pipelines across AWS, GCP, and Kubernetes, focusing on reliability, scalability, and observability. I excel at data engineering, model deployment, and automating CI/CD processes using TensorFlow, MLflow, Terraform, and Docker. I collaborate with data scientists, engineers, and operations teams to deliver high-quality ML solutions with measurable impact.

I enjoy bridging gaps between disciplines to accelerate delivery while maintaining governance and security. My track record includes reducing deployment time, improving model reliability, and delivering cost savings through automation and efficient workflows.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
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Work Experience

Machine Learning Platform Engineer at Fractal
January 1, 2025 - November 25, 2025
Led the development of an AWS-based ML infrastructure supporting 40+ workloads with 99.9% uptime. Built and automated ML pipelines using TensorFlow and MLflow, achieving 40% faster deployments, 25% accuracy gains, and saving 300 hours annually in manual tasks. Implemented model monitoring and drift detection with Prometheus and Grafana, reducing drift detection time by 40% and increasing model performance by 25% within 6 months. Optimized Docker environments, recovered 50 GB storage, and improved deployment efficiency by 25%. Drove scalability improvements and delivered 12 training sessions to boost MLOps adoption.
Software Engineer (DevOps / MLOps) at IBM
October 1, 2023 - October 1, 2023
Automated CI/CD pipelines, improving deployment speed by 40% and enabling seamless integration of ML models into production. Built IaC using Terraform and Ansible, established comprehensive monitoring with Prometheus and Grafana, reducing incident response times by 25%. Optimized cloud-based applications for a 20% performance increase and lower costs. Mentored junior engineers on DevOps and MLOps best practices.

Education

Master of Science in Computer Science at The George Washington University
January 11, 2030 - May 1, 2025

Qualifications

AWS Certified Machine Learning - Amazon
January 11, 2030 - November 25, 2025
Google Cloud Professional ML Engineer - Google
January 11, 2030 - November 25, 2025

Industry Experience

Software & Internet