Tamogh Nekkanti profile photo 1 on Tal

Tamogh Nekkanti

MLE@BlackRock

Patiala

4+ years of work experience

BlackRock
Jul 20251 yr 2 mosPresent

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.
BlackRock
Jan 20257 mosJul 2025

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.
Google Summer of Code
Apr 20246 mosSep 2024

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
Thapar Satellite Program (ThapSat)
Feb 20222 yrs 6 mosJul 2024

India

Worked as a Student Engineer intern at Image Processing Department.Worked on soil moisture detection algorithms and image compression algorithms such as LZW
GitHub
@Tamogh123

Tamogh’s AI Stack

github copilot
github copilot
hugging face
hugging face
ollama
ollama
llama.cpp
llama.cpp
OpenRouter
OpenRouter
vLLM
vLLM

Education

Thapar Institute of Engineering & Technology

Bachelor of Technology - BTech, Computer Science

Thapar Institute of Engineering & Technology

20214 yrs2025

12th

City pu college

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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