Tamogh
I'm a Machine Learning Engineer
Building unified ML platforms at BlackRock — from open-source research to multi-cloud production inference.
01. About me
Building the future
one model at a time
I'm a Machine Learning Engineer at BlackRock building a unified ML platform for registering, training, tuning, and deploying models across multi-cloud environments at production scale.
My stack spans Rust, KServe, KEDA, Azure, and PyTorch. I was also a Google Summer of Code 2024 contributor, having integrated MCMC and Variational Inference into Neuroptimus for neuronal parameter estimation
Completed a B.E. in Computer Science at Thapar Institute of Engineering & Technology
$ cargo run --release -- deploy --model gpt2-ft
Building Docker runtime from user deps... ✓
Pushing to Azure Container Registry... ✓
Deploying via KServe on AKS...
Health check: pod/gpt2-ft-0 Running ✓
KEDA autoscaler: minReplicas=1 maxReplicas=20
Inference endpoint live → /v1/models/gpt2-ft ✓
Metrics streaming → Prometheus + Grafana
$
02. Skills
Technical Arsenal
From research to deployment — the full ML lifecycle.
ML / AI
Systems & Backend
Cloud & MLOps
Arch. & Design
Topics & Domains
03. Projects
Things I've Built
Production ML systems, research prototypes, and everything in between.
Unified ML Platform — BlackRock
Production ML platform to register, train, tune, evaluate, and deploy open-source, proprietary, and third-party models across multi-cloud. Backend in Rust with DDD, KServe for serving, KEDA for event-driven autoscaling. Delivers model inference-as-a-service with full lifecycle monitoring via Grafana & Prometheus.
ETL Pipeline Framework — BlackRock
Production-grade ETL pipelines for financial data forming the backbone of a trade library. Built a test server framework enabling rapid creation and validation of pipelines without manual environment setup. Integrated LLM-based capabilities into legacy data workflows.
Bayesian Inference — GSoC 2024
Integrated MCMC and Variational Inference into Neuroptimus for neuronal parameter estimation under Dr. Sbalocz Kali at Google Summer of Code. Implemented global optimization techniques and custom loss functions for improved convergence.
Chemical Reaction Prediction
Hybrid architecture combining Graph Attention Networks and Transformers to predict chemical reaction outcomes. Built local + global molecular embeddings capturing both structural and relational properties. Achieved 74% prediction accuracy.
Soil Moisture Prediction — ThaparSat / ISRO
CNN-based soil moisture prediction model trained on satellite-derived features under the ISRO program. Includes denoising algorithms for satellite-retrieved data and payload compression pipelines.
Motion Amplification & Frequency Analysis
Phase-based motion amplification and frequency extraction from video streams. Smart India Hackathon 2023 Finalist. Achieved 88% accuracy in micro-motion signal detection from raw video using FFT-based analysis.
04. Experience
Where I've Worked
Machine Learning Engineer
BlackRock
Building a unified ML platform to register, train, tune, evaluate, and deploy open-source, proprietary, and third-party models across multi-cloud environments. Architected backend systems using Domain-Driven Design in Rust. Developed a custom model deployment service generating Docker runtimes dynamically. Orchestrating production inference with KServe and KEDA. Monitoring via Grafana and Prometheus.
Software Developer Intern
BlackRock
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 for rapid creation and validation of ETL pipelines without manual setup.
Open Source Developer (GSoC 2024)
Google Summer of Code · Neuroptimus
Integrated Bayesian inference methods — MCMC and Variational Inference — into Neuroptimus for neuronal parameter estimation under mentor Dr. Sbalocz Kali. Implemented global optimization techniques and custom loss functions for improved convergence and accuracy.
Student Engineer Intern — ThaparSat
ISRO Program · Thapar University
Developed a soil moisture prediction model based on CNNs and other architectures using satellite-derived features under mentor Dr. Mamta Gulati. Worked on denoising algorithms for satellite-retrieved data and payload compression pipelines.