Amulya Gupta — Senior Software Engineer

I'm an ML engineer who works on the parts that come after the model is trained. Most ML work stops at the notebook. I'm interested in what happens next — packaging the model, building the API, wiring up the pipeline, deploying to a real cluster, and knowing when something breaks at 2am. That's the gap I work in. My stack is Python-first: FastAPI for inference services, MLflow for experiment tracking and model registry, Prefect for pipelines, Docker and Kubernetes for deployment, Prometheus and Grafana for observability. Not because these are fashionable — because I've felt the pain of shipping without them. Lately I've been going deep on GenAI and agentic systems. RAG pipelines specifically — where the hard problems aren't the model, they're retrieval quality, context management, latency under real load, and making the whole thing behave predictably when users do unexpected things. I'm pursuing an M.Tech in AI/ML at BITS Pilani, which mostly means I get to break things in coursework before I break them in production. Long-term, I want to work on AI infrastructure at scale — the platforms and serving layers that let teams actually ship ML instead of just demo it.

Stackforce AI infers this person is a Backend-heavy Fullstack Engineer specializing in MarTech and SaaS solutions.

Location: Noida, Uttar Pradesh, India

Experience: 6 yrs 7 mos