MLOps Engineer | 1+ Year | Kubernetes, Docker, CI/CD, Cloud ML

I am an MLOps / ML Engineer with hands-on experience building, deploying, and operating production-grade AI/ML systems. I work at the intersection of machine learning, cloud infrastructure, and DevOps, focusing on reliable, scalable, and observable ML services.

What I Do

• Design and deploy ML pipelines using Python, PyTorch/TensorFlow, and scikit-learn
• Build containerized ML services using Docker and deploy them on Kubernetes
• Work extensively with GCP, including Vertex AI, model training pipelines, and inference endpoints
• Develop GenAI and NLP systems using LangChain, FastAPI, and LLM APIs
• Implement CI/CD pipelines, automation, and cloud-native best practices
• Set up monitoring and logging using Prometheus, Grafana, and cloud logging tools
• Troubleshoot production issues across infrastructure, networking, and application layers

Mindset

I’m a pragmatic builder who values systems that work reliably in production over experimental prototypes. I enjoy debugging complex issues, improving system resilience, and continuously learning about MLOps, distributed systems, and applied AI.