---
title: "Tamogh Nekkanti - Machine Learning Engineer I in Patiala | Tal"
description: "Meet Tamogh Nekkanti, MLE@BlackRock based in Patiala. AI stack includes github copilot, hugging face, and ollama. Explore public work links including github."
image: "https://tal.club/meet/tamogh-nekkanti/share-image"
---

# Tamogh Nekkanti on Tal

## Headline

MLE@BlackRock

## About

I'm a Machine Learning Engineer at BlackRock, where I build cloud\-native platforms for training, deploying, and serving machine learning models at scale\. My work focuses on ML infrastructure, distributed systems, and inference platforms, building production systems in Rust and Kubernetes\. I work on modern LLM serving and inference infrastructure using NVIDIA Dynamo, KServe, and inference runtimes such as vLLM, TensorRT\-LLM, NVIDIA Triton Inference Server, and TorchServe\. My work includes deployment automation, inference orchestration, distributed build systems, autoscaling, observability, and cloud\-native infrastructure on Azure\. Previously, I interned at BlackRock, where I built production ETL systems and integrated LLM\-powered workflows\. I was also a Google Summer of Code 2024 contributor, implementing Bayesian inference and optimisation algorithms for computational neuroscience, and have contributed to the ThaparSat–ISRO programme, developing machine learning solutions for satellite imagery\.

## Location

Patiala

## AI stack

github copilot

hugging face

ollama

llama\.cpp

OpenRouter

vLLM

## Work experience

Machine Learning Engineer I at BlackRock, Jul 2025 \- Present · 1 yr 2 mos, Designed a unified ML platform for model training, tuning, deployment, and lifecycle management across multi\-cloud environments\. Built model serving workflows using KServe and NVIDIA Dynamo, supporting vLLM, TensorRT\-LLM, Triton Inference Server, and TorchServe\. Developed high\-performance Rust services for inference orchestration, job scheduling, and automated DynamoGraph deployment generation\. Built a deployment framework to package agent code, model assets, dependencies, and serving runtimes into reproducible production containers\. Engineered event\-driven inference infrastructure using KServe, KEDA, Prometheus, and Grafana\. Developed a distributed container image build pipeline with Argo Workflows, Azure Container Registry, and Wiz security scanning\. Built a resumable upload service using tusd supporting 100 GB\+ uploads and optimized the build infrastructure to run within 20% memory usage on 500m CPU\.

Software developer intern at BlackRock, Jan 2025 \- Jul 2025 · 7 mos, Developed and optimized ETL pipelines for financial data, forming the backbone of a production\-grade trade library\. Modernized legacy systems by integrating LLM\-based capabilities into data workflows\. Built a test server framework to enable rapid creation and validation of ETL pipelines without manual setup\.

Open Source contributor at Google Summer of Code, Apr 2024 \- Sep 2024 · 6 mos, Remote, Inference based methods integration into Neuroptimus\.Implemented algorithms such as Bayesian inference using MCMC , Variational inference models and likelihood\-free methods such Approximate Bayesian Computation

Student engineer intern at Thapar Satellite Program \(ThapSat\), Feb 2022 \- Jul 2024 · 2 yrs 6 mos, India, Worked as a Student Engineer intern at Image Processing Department\.Worked on soil moisture detection algorithms and image compression algorithms such as LZW

## Education

Bachelor of Technology \- BTech, Computer Science, Thapar Institute of Engineering & Technology

12th, City pu college

## Public links

- github: https://github\.com/Tamogh123

[View the original profile](https://tal.club/meet/tamogh-nekkanti)

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