---
title: "Lankesh Purekar - Sr. Machine Learning Engineer in Pune District | Tal"
description: "Meet Lankesh Purekar, Sr. Machine Learning Engineer@_VOIS | VNIT M.Tech CSE (2021-23) | Citi Innovation Challenge 4.0 hackathon Runner-up | GATE AIR 1321 based in Pune District. AI stack includes antigravity and codex."
image: "https://tal.club/meet/lankesh-purekar/share-image"
---

# Lankesh Purekar on Tal

## Headline

Sr\. Machine Learning Engineer@\_VOIS \| VNIT M\.Tech CSE \(2021\-23\) \| Citi Innovation Challenge 4\.0 hackathon Runner\-up \| GATE AIR 1321

## About

Senior ML Engineer with 4\+ years building and shipping production ML and GenAI systems at scale, leveraging the power of AWS cloud technologies\. At VOIS, I own the end\-to\-end ML lifecycle for 15\+ live use cases on the Financial platform — from feature engineering, Model Training to Optimization and AWS deployment\. I've cut training times by 88%, reduced infrastructure costs by 48%, and designed RAG\-PAL based GenAI systems from the ground up\. M\.Tech from VNIT Nagpur \| GATE AIR 1321

## Location

Pune District

## AI stack

antigravity

codex

## Work experience

Sr\. Machine Learning Engineer at \_VOIS, Aug 2023 \- Present · 3 yrs 1 mo, Pune District, Architected the team\-wide reference ML pipeline on AWS SageMaker \(Spark Processing → Feature Engineering → Training → Inference → Post\-Processing\), adopted as the standard framework across all Data Scientists in the organization within the AWS\. Owned end\-to\-end ML lifecycle for 15\+ production use cases on the high\-volume Financial platform — spanning problem framing, data ingestion, feature engineering, model training, AWS deployment, drift monitoring, and post\-production maintenance\. Delivered an 88% reduction in training time \(34 hrs → 4 hrs\) for 477 site\-level models by redesigning the pipeline with parallel multi\-core training on high\-compute AWS instances, simultaneously cutting infrastructure costs by 26%\. Reduced prediction latency by >90% and pipeline cost by 34% through multiprocessing and horizontal/vertical scaling strategies across multiple high\-volume use cases\. Designed and deployed a RAG\-based QnA system for European stock market analysis — built the full document ingestion, chunking, embedding, and LLM generation stack to deliver context\-grounded answers on market trends\. Built a data drift detection pipeline with automated profiling and reporting, enabling proactive model maintenance and improving production reliability across all deployed use cases\. Achieved 48% reduction in dev account operational costs and 32% storage savings by building CloudFormation \+ tagging\-based automation to detect and eliminate unused AWS resources and standardize S3/EFS data storage\.

Subject Matter Expert \(Computer Science\) at HW Saver LLP, Jun 2021 \- Sep 2021 · 4 mos

Assistant System Engineer at Tata Consultancy Services, Jul 2019 \- Nov 2020 · 1 yr 5 mos, Nagpur, Maharashtra, India

## Education

Master of Technology \- MTech, Computer Engineering, Visvesvaraya National Institute of Technology

Bachelor of Technology, Information Technology, Government College of Engineering, Amravati\.

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

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