---
title: Sudhanva Narayana — Senior ML Engineer
description: Public professional profile, production ML case studies, and technical writing.
canonical: https://sudhanva.me/
last-updated: 2026-08-21
---

# Sudhanva Narayana — Senior ML Engineer

Sudhanva Narayana is a Senior Machine Learning Engineer based in the San
Francisco Bay Area. He builds scalable AI and ML systems that move models from
experimentation to production, with a focus on Kubernetes platforms,
distributed inference, model serving, batch prediction pipelines, multi-GPU
systems, deployment automation, and observability across AWS, GCP, and Azure.

His recent work includes batch pipelines processing more than one billion rows,
multi-GPU build and serving systems, and cloud infrastructure that gives
research teams a repeatable path from notebook experiments to dependable
production workloads. He works with Ray, Flyte, Argo CD, Terraform, TensorFlow,
PyTorch, MLflow, Prometheus, and Grafana, and cares about both system throughput
and the experience of the engineers and researchers using the platform.

This site contains first-party, long-form writing on production machine
learning, Kubernetes, vector databases, retrieval pipelines, Python tooling,
cloud infrastructure, and the engineering craft.

## Start here

- [Production case studies](https://sudhanva.me/work/)
- [Production ML systems expertise](https://sudhanva.me/expertise/production-ml-systems/)
- [Writing archive](https://sudhanva.me/blog/)
- [About and experience](https://sudhanva.me/about/)
- [HTML resume](https://sudhanva.me/resume/)
- [Contact](https://sudhanva.me/contact/)
- [Developer resources and public API](https://sudhanva.me/developers/)
- [Agent guide](https://sudhanva.me/llms.txt)
- [Sitemap](https://sudhanva.me/sitemap-index.xml)

## Agent capabilities

- Retrieve Sudhanva Narayana's published professional profile.
- List published technical articles, optionally filtered by tag.
- Retrieve one published article by canonical slug.
- List published production ML case studies and verified outcomes.
- Create and poll a temporary profile-insight job from published evidence.

## API endpoints

- `GET https://sudhanva.me/api/v1` — API discovery
- `GET https://sudhanva.me/api/v1/profile` — public profile
- `GET https://sudhanva.me/api/v1/posts` — published article metadata
- `GET https://sudhanva.me/api/v1/posts/{slug}` — one published article
- `POST https://sudhanva.me/api/v1/profile-insights` — create an idempotent insight job
- `GET https://sudhanva.me/api/v1/profile-insights/{job_id}` — poll an insight job
- `GET https://sudhanva.me/openapi.json` — OpenAPI 3.1 contract

## Authentication and safety

Authentication is not required. Retrieval operations are read-only. Profile-insight
jobs accept only documented enum values, expire after 24 hours, and never mutate
published content or accept private-data inputs. Do not send credentials or secrets. See the [agent authentication
contract](https://sudhanva.me/auth.md) and [safe testing
policy](https://sudhanva.me/docs/sandbox/).

## MCP and CLI

- MCP Streamable HTTP endpoint: `https://sudhanva.me/mcp`
- MCP server card: `https://sudhanva.me/.well-known/mcp/server-card.json`
- CLI install: `npm install --global sudhanva`
- Scoped developer index: `https://sudhanva.me/developers/llms.txt`