π MLOps & Backend Engineer
Building production-grade ML platforms and cloud-native backend systems that are scalable, reliable, and observable.
- 4+ years of experience across MLOps, ML platforms, and backend engineering
- Strong focus on end-to-end ML lifecycle β training, deployment, monitoring, retraining
- Experienced in Kubernetes-first, cloud-native architectures
- Enjoy working at the intersection of Machine Learning, Backend Engineering, and Cloud Infrastructure
I like turning complex systems into simple, maintainable, and production-ready solutions.
Languages
Python β’ SQL β’ Bash
MLOps & ML Platforms
Kubeflow β’ Airflow β’ MLflow β’ Evidently AI β’ WhyLabs β’ Vertex AI β’ SageMaker
Backend Engineering
FastAPI β’ Flask β’ REST APIs β’ Microservices β’ OAuth2
Data Engineering
PySpark β’ BigQuery β’ Pandas
Infrastructure & DevOps
Kubernetes β’ Docker β’ Terraform β’ GitHub Actions β’ Jenkins
Cloud
GCP β’ AWS
- Clean architecture over quick hacks
- Monitoring and observability are first-class citizens
- Reproducibility beats notebook-only workflows
- Systems should fail early, clearly, and safely
- πΌ LinkedIn: https://www.linkedin.com/in/arijitiiest/
- π Portfolio: https://arijitiiest.github.io
- βοΈ Medium: https://medium.com/@arijit_chowdhury
- π§ Email: arijitchowdhury8926@gmail.com

