ML Engineer • MSCS (AI) @ Georgia Tech

Engineering visionary AI systems & scalable ML solutions

I design, automate, and scale machine learning platforms, and I love shipping things that are fast, robust, and actually useful.

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CloudAzure, AWS, GCP, ADF, AML
DataSpark, Databricks
MLSklearn, PyTorch, Tensorflow, Pandas, PySpark
OpsDocker, CI/CD, Kubernetes, Jenkins, Splunk, Dynatrace, New Relic

About Me

Quick snapshot of who I am and what I enjoy working on.

Hi! I’m Tejasvi, a Toronto-based ML Platform Engineer pursuing an MS in CS - specializing in Artificial Intelligence. With a bottom-up perspective on ML infrastructure, I’ve handled everything from VM setup and DevOps agent configuration to ADF SHIR integration and pipeline orchestration, establishing strong underpinnings for enterprise-grade ML systems. I’ve built Azure and Databricks‑based pipelines, automated secrets and deployments, and partnered with data science teams to productionize models safely. Outside work, I’m into DJing, karaoke, and building quirky ML tools.

Currently: ML Platform Engineer @ Canada Life
Degree: BSc CS (WLU), MSCS (GT)
Looking for: Fun projects that make a difference
Interests: ML, MLOps, Recommender Systems, LLMs, NLP, Linguistics, Ethics

Credentials

Education & experience

ML Platform Engineer - Canada Life

2024 — Present • Toronto, ON

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Automated Databricks Secrets & pipeline deployments via CI/CD (Gitlab, ADF).
Productionized models with monitoring, alerting, and rollback strategies.
Partnered with DS to reduce training runtime 40% via Spark tuning & caching.

M.S. Computer Science (ML) - Georgia Tech (MSCS)

2023 — Present • Specialization: Artificial Intelligence

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Courses: ML for Trading, Cognitive Science, AI Ethics & Society, NLP, KBAI.
Projects: Spotify subgenre discovery (EM, K‑Means, PCA/ICA), Analogical Reasoning Assistant.

B.Sc. Computer Science - Wilfrid Laurier University

2016 — 2020 • Co‑op

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Developed an automated system for handwriting detection
Built a voice assistant using DialogFlow that predicts sentiment analysis score using NLP

Projects

Coming soon....

Databricks Secrets Automation

Gitlab + Databricks + ADF pipelines to sync secrets and orchestrate deployments safely.

Python ADF Databricks

Preview Code

Spotify Subgenre Discovery

Unsupervised learning (EM, K‑Means, PCA/ICA) to uncover latent subgenres from audio features.

EM K‑Means PCA/ICA

Preview Code

Blog

My two cents on the current state of AI

Are we getting overdependent on AI?

Projects

Discovering Spotify subgenres

A short write‑up of results and what surprised me.

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