chinamy machine_learning
@chinamymachine_learn
Backend and AI-focused software engineer building scalable cloud-native systems.
What I'm looking for
I am a software engineer specializing in backend systems and AI-driven applications, focused on building high-performance, cloud-native services. I bring hands-on experience with FastAPI, Django, distributed microservices, and production deployment on Google Cloud.
At NewGen Softech and Nebuzora Studios, I developed scalable REST APIs, implemented PostgreSQL data layers with Redis caching, and configured Google Cloud load balancing and API gateway services to ensure fault tolerance and high availability.
My projects include a published research system — a multi-AI agent empathy platform — and a patented medical tourism application built with event-driven microservices, Kafka, Docker, and monitoring via Grafana. I have practical experience deploying RAG pipelines and agentic AI workflows on Vertex AI.
I am passionate about delivering reliable, secure systems that scale to thousands of users, and I prioritize clean engineering, observability, and collaboration using Git-based workflows.
Experience
Work history, roles, and key accomplishments
Software Engineer Intern
NewGen Softech
Feb 2026 - Present (1 month)
Built and deployed a full-stack web application using Python and Django, developing scalable backend services and improving cross-platform UX with responsive front-end components; managed collaborative development via Git.
Software Engineer Intern
Nebuzora Studios
Oct 2025 - Dec 2025 (2 months)
Designed and implemented scalable backend services with FastAPI, PostgreSQL and Redis; configured Google Cloud load balancing and API gateway for high availability and built RAG-based AI customer query engine on Vertex AI.
Education
Degrees, certifications, and relevant coursework
New Horizon College of Engineering
Bachelor of Engineering, Artificial Intelligence and Machine Learning
2022 - 2026
Grade: 9.14/10
Pursuing a Bachelor of Engineering in Artificial Intelligence and Machine Learning with a CGPA of 9.14/10, focused on AI systems, backend development, and cloud-native deployments.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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