I'm Amulya Gupta, an MLOps & Python AI engineer based in Noida, India. I currently work as a Senior Software Engineer at HCLTech, where I've owned and delivered production systems at a scale most engineers only read about โ 20M+ users, 40+ campaigns, zero critical post-launch issues.
My path into AI engineering started at BITS Pilani, where I completed my M.Sc. and developed a deep curiosity for data systems. After graduating, I joined Classplus as a Software Engineer, migrating a monolith to microservices and building ETL pipelines that powered real-time dashboards. That experience taught me one lesson I carry everywhere: reliable data infrastructure is the foundation of every good AI system.
Today, I'm back at BITS Pilani pursuing my M.Tech in Artificial Intelligence & Machine Learning while working full-time, deepening my expertise in distributed systems, deep learning, and ML data management. Outside of work, I build MLOps projects end-to-end โ because I believe the best way to learn production AI engineering is to actually do it.
My goal: to be the engineer who doesn't just train models, but ships them โ reliably, observably, and at scale. If that sounds like what your team needs, let's talk.
What I Build With
MLOps & Infra
- MLflow
- Docker
- Kubernetes
- GitHub Actions
- Prometheus
- Grafana
Backend & APIs
- Python
- FastAPI
- Node.js / Express
- REST APIs
- Pydantic
Data & Pipelines
- Prefect
- PostgreSQL
- MySQL
- ETL Pipelines
- AWS S3 / EC2
ML & AI
- scikit-learn
- TensorFlow
- PyTorch
- LLM Fine-tuning
- RAG Pipelines
Academic Background
M.Tech in Artificial Intelligence & Machine Learning (WILP)
Birla Institute of Technology and Science (BITS), Pilani
Coursework: Distributed Systems, Deep Learning, Data Management for ML
M.Sc. General Studies (Data Science Minor)
Birla Institute of Technology and Science (BITS), Pilani
Professional Certifications
Prompt Engineering Level 3
Percipio ยท Advanced prompting patterns, multi-step reasoning, constraints, safety & evaluation
Generative AI Fundamentals
Percipio ยท LLMs, embeddings, tokenization, context windows, evaluation basics
AWS Cloud Practitioner
Percipio ยท IAM, EC2, S3, CloudWatch, Billing Explorer โ Training completed, exam in progress