---
title: "Yash Gupta - MLOps Engineer in Bengaluru | Tal"
description: "Meet Yash Gupta, MLOps Engineer @F-Secure based in Bengaluru. AI stack includes claude code, cursor, and langchain."
image: "https://tal.club/meet/yash-gupta-12/share-image"
---

# Yash Gupta on Tal

## Headline

MLOps Engineer @F\-Secure

## About

MLOps Engineer with about 4 years of experience, passionate about building scalable, automated, and production\-ready ML infrastructure\. Experienced in designing and optimizing data pipelines, automating model training and evaluation, and deploying ML systems across multi\-cloud environments\. Skilled in Kubernetes, AWS, Ray, and Dagster, with a strong focus on CI/CD, monitoring, and workflow orchestration\. Adept at developing internal tools that empower ML scientists by streamlining infrastructure access and enforcing best practices\. Seeking opportunities to drive operational excellence in ML systems and enable seamless experimentation\-to\-production transitions\. To get in touch, mail me at yashgupta0373@gmail\.com

## Location

Bengaluru

## AI stack

claude code

cursor

langchain

huggingface

Deepgram

vLLM

## Work experience

MLOps Engineer at F\-Secure Corporation, Jul 2025 \- Present · 1 yr 3 mos, Bengaluru, Karnataka, India, • Built the WhatsApp Scam Detection Chatbot backend from the ground up — a production AI service that lets partner apps offer real\-time scam analysis over WhatsApp for text, URLs, and images, deployed through staging to production on AWS\. • Owned cloud infrastructure and MLOps for F\-Secure’s scam\-protection AI portfolio — designing CDK\-based deployments, CI/CD pipelines, multi\-region active\-active setups, and production runbooks across Scam Scanner, OCR, and content enrichment services\. • Shipped the AI content enrichment pipeline for Scam News, turning raw security articles into personalized, safety\-focused content for mobile users — including automated quality checks on generative AI outputs before they reach end users\. • Improved production reliability and scale of scam\-detection systems through load testing, performance tuning, observability \(Dynatrace, CloudWatch\), and fixes for high\-traffic failure modes — keeping AI services stable under real\-world usage\. • Built privacy\-compliant data pipelines for SMS protection, including PII anonymization, feedback processing, and secure data flows that support model improvement without exposing user data\. • Drove security and engineering standards across AI services — vulnerability remediation, security triage for new systems, architecture documentation, and cross\-team API contracts between AI and backend teams\.

MLOps Engineer at Sanas, Aug 2023 \- Jul 2025 · 2 yrs, • Built and maintained an ETL pipeline for ML model training using Dagster, Ray, Polars, DeltaLake, and EFS on AWS EKS, automating data and feature engineering while enabling continuous model training via Weights & Biases\. • Developed a scalable automated model evaluation platform leveraging Celery, FastAPI, Ray, SQS, and PostgreSQL on EKS, featuring a Go\-based CLI frontend and Slack integration for real\-time monitoring and collaboration\. • Designed and developed a multi\-cloud model training CLI using Python, Typer, Poetry, OmegaConf, and MongoDB, enabling seamless resource provisioning across AWS, on\-prem infrastructure, and extending compatibility with other cloud providers\. • Developed and delivered utility libraries for model training, simplifying infrastructure access and enhancing coding efficiency for ML scientists while enforcing standardized MLOps best practices and optimizing experiment workflows\. • Built an end\-to\-end data collection and PII redaction tool deployable on customer cloud infrastructure, featuring a web app, speech\-to\-text, and on\-prem PII removal for compliance\.

Software Engineer at Sanas, Jul 2022 \- Aug 2023 · 1 yr 2 mos, • Designed and implemented end\-to\-end data pipelines, migrating from local scripts to scalable AWS\-based solutions using Lambda, S3, SQS, CloudWatch, PostgreSQL, and Deepgram, scaling up processing capacity by 100×\. • Automated internal workflows, eliminating manual processes and increasing team productivity by 5× through Python\-based automation and CI/CD integrations\. • Developed monitoring dashboards using Power BI, Amazon QuickSight, and custom web apps to track data pipeline performance and system health\. • Evaluated and integrated multiple ASR \(Automatic Speech Recognition\) systems, optimizing speech\-to\-text accuracy for production workloads\. • Enhanced internal infrastructure by adding features to data collection tools, model evaluation tools, and QA platforms, improving system reliability and usability\.

## Education

Bachelor of Technology \- BTech, Electronics and Telecommunication Engineering, Assam

HSC / Intermediate, PCM and Computer Science, Salt Brook Academy \- India

[View the original profile](https://tal.club/meet/yash-gupta-12)

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