Team Lead ML Ops@ Eaton
7 Years of Experience
Pune, Maharashtra, India
+9187********
45
35
60 Days
I have graduated from IIT Kanpur [B.Tech & M.Tech]. I am a keen problem solver. I am very calm in whatever situation it might be
Eaton, Others, Computer Software
Eaton
Eaton India Innovation Center
Eaton, Eaton, Eaton India Innovation Center, DMG MORI-IIT INTERNSHIP PROGRAM, The University of Tokyo, Tokyo (Japan), Boeing-Cyient Externship Program
Job Title : Team Lead Machine Learning Operations
Company name : Eaton
Period : July 2023 - Present
Summary : Leading a team of 5 engineers to develop Brightlayer Analytics Services Platform on Azure with end to end MLOps Features for Eaton Digital Offerings
Location : Pune, Maharashtra, India
Job Title : Senior Engineer
Company name : Eaton
Period : May 2021 - July 2023
Summary : MLOps Senior Engineer
MLOps Features for Brightlayer Analytics Services
Developed a generic wrapper over weights & biases and logging as a initiative to standardize logging across different developments
Implemented features for Experimental Tracking, Model, Feature Storage & their versioning. Defined the software release strategy
Looked into Model Monitoring in Production. Evaluated Why Logs, Evidently AI etc. and mapped drift algorithms to datasets
Developed templates for standardizing and promoting containerized development of models for reducing time to production
Defined the ML Ops maturity levels for the team. Interacted with Cross functional teams for the adoption of the these libraries
Evaluated the requirements, defined different metrics for Data Quality and Data Readiness and evaluated multiple tools for it
Data Ops for Brightlayer Analytics Services
Finalized Great Expectations module for Data Quality. Identified multiple adopters for Data Quality on the BAS Platform
Used One flow branching strategy and created pipeline for Data Quality with configs in Cosmos DB and DAGs with Airflow
Aerospace Predictive Maintenance [Senior Data Scientist]
ML Engineer leading Predictive Maintenance project aimed to improve internal productivity of Eaton’s Aerospace MRO Sites
Created automated data pipelines to get SQL table for features. Created scripts to automate pdf data conversion to SQL tables
Created branching strategy for the project. Created CI/CD pipeline for containerized deployment using Docker
Got the solution architecture approved from IT for Cloud deployment using Azure Kubernetes cluster and SQL Server
Developed Time series based forecasting algorithms using FLAML for inventory, warranty claims and returns prediction
Location : Pune, Maharashtra, India
Job Title : Engineer
Company name : Eaton India Innovation Center
Period : August 2017 - May 2021
Summary : Project lead for an AI/Cost out project on Drawing and Process sheet digitization using Optical Character Recognition
Estimated NRE cost out saving of 300 dollars per legacy drawing/500 dollars per process sheet once the tool is deployed
Used concept of transfer learning and deployed using streamlit by training YOLO algorithm for text localization
Used pytesseract library for text detection. Also trained a NLP model (CRNN) to detect the texts from the localization
Introduced few digitalization campaigns in Aerospace Group. Conducted a brainstorming session to introduce Aero team to machine learning and to discuss possible applications in Aero
Finance Invoicing:
Led an AI project to automate the complex invoicing process which will help the team save 70% of time every month
Helped the finance team to establish a SQL database. This will help for a faster query of the data compared to excel
Developed a PowerBI dashboard to aid visualization and analysis of the data. The project was well appreciated by the Eaton LT
Seal Guru [Nominated for Aerospace CI award]:
Project lead [Backend] for an AI project Seal guru for segmented seal design which will help in estimated $140k saving annually
Implemented end to end seal design automation with preliminary drawings to reduce the TAT from 1 month to 2 Days
Implemented Variation analysis module from scratch to get min-max variation of all the CTQ specs to get failure probability
Created a robust database using the seals in production to assist decision making based on past designed seal performances
Product Design and Automation
Part of Design team for Eaton Aerospace Products. Automated Design and Drawing creation for various Aerospace Products
Introduced Parametric Models & drawings to reduce the TAT significantly for the product Design. Supported Sustaining Engg.
Used Agile & PROLaunch principles, Designed, tested & Increased the product capability to venture the Large diameter seal business
Location : Pune Area, India
Job Title : Summer Intern
Company name : DMG MORI-IIT INTERNSHIP PROGRAM
Period : July 2016 - July 2016
Summary : The internship aimed at design and strength evaluation of the ATC bracket used in DMG Mori NTX 1000. I incorporated the effect(thickness change) caused by casting in the analysis process. The design and strength evaluation was completed using Creo Parametric. Achieved a weight reduction of 41% in the current design of the ATC bracket.
Location : Iga, Mie Prefecture,Japan
Job Title : Summer Research Intern
Company name : The University of Tokyo, Tokyo (Japan)
Period : May 2016 - July 2016
Summary : The Internship aimed at applying non-linear material behavior for strength evaluation of Hydrogen pressure vessel using Finite Element Method. We modeled Aluminum Liner used in a pressure vessel using Elasto-Plastic behaviour. K-Supercomputer was used to run the Simulation and EnSight was used for Post Processing the output files.
Location : Within 23 wards, Tokyo, Japan
Job Title : Summer Research Intern
Company name : Boeing-Cyient Externship Program
Period : May 2015 - July 2015
Summary : The work was inspired from Prof. Stephane Bordas's work on Isogeometric analysis. The research Internship aimed at designing and validating a method which can be used as a substitute for conventional meshing used in Finite Element Analysis.
Title : Introduction to Big Data with Spark and Hadoop
Period : February 2024 - Present
Summary : 93P4ZZP3HN5D, coursera.org, https://www.coursera.org/account/accomplishments/records/93P4ZZP3HN5D
Issuing Authority : IBM
Title : Generative AI with Large Language Models
Period : January 2024 - Present
Summary : 7FA6WKBR5FR4, coursera.org, https://www.coursera.org/account/accomplishments/records/7FA6WKBR5FR4
Issuing Authority : DeepLearning.AI, Amazon Web Services
Title : Machine Learning with Apache Spark
Period : January 2024 - Present
Summary : A4LJB9VDKS3H, coursera.org, https://www.coursera.org/account/accomplishments/records/A4LJB9VDKS3H
Issuing Authority : IBM
Title : Machine Learning Engineering for Production (MLOps) Specialization
Period : December 2023 - Present
Summary : 9MQUJGBSHQUV, coursera.org, https://www.coursera.org/account/accomplishments/specialization/9MQUJGBSHQUV
Issuing Authority : DeepLearning.AI
Title : Natural Language Processing with Classification and Vector Spaces
Period : May 2021 - Present
Summary : 2L42KM7DKHTH, coursera.org, https://www.coursera.org/account/accomplishments/records/2L42KM7DKHTH
Issuing Authority : DeepLearning.AI
Title : Build Better Generative Adversarial Networks (GANs)
Period : February 2021 - Present
Summary : JE7WDXVYMMJP, coursera.org, https://www.coursera.org/account/accomplishments/records/JE7WDXVYMMJP
Issuing Authority : DeepLearning.AI
Title : Prediction and Control with Function Approximation
Period : February 2021 - Present
Summary : U268QBXBM4NW, coursera.org, https://www.coursera.org/account/accomplishments/records/U268QBXBM4NW
Issuing Authority : University of Alberta, Alberta Machine Intelligence Institute
Title : Build Basic Generative Adversarial Networks (GANs)
Period : November 2020 - Present
Summary : 7KMKE7AGQXHE, coursera.org, https://www.coursera.org/account/accomplishments/records/7KMKE7AGQXHE
Issuing Authority : DeepLearning.AI
Title : Sample-based Learning Methods
Period : November 2020 - Present
Summary : FGF3G82L5M7F, coursera.org, https://www.coursera.org/account/accomplishments/records/FGF3G82L5M7F
Issuing Authority : University of Alberta, Alberta Machine Intelligence Institute
Title : Fundamentals of Reinforcement Learning
Period : October 2020 - Present
Summary : B8A43ZW72NBL, coursera.org, https://www.coursera.org/account/accomplishments/records/B8A43ZW72NBL
Issuing Authority : University of Alberta, Alberta Machine Intelligence Institute
Title : Deep Neural Networks with PyTorch (with Honors)
Period : August 2020 - Present
Summary : QPNB79CPDECP, coursera.org, https://www.coursera.org/account/accomplishments/records/QPNB79CPDECP
Issuing Authority : IBM
Title : Python Project: pillow, tesseract, and opencv
Period : August 2020 - Present
Summary : J5YVKHF7GMLM, coursera.org, https://www.coursera.org/account/accomplishments/records/J5YVKHF7GMLM
Issuing Authority : University of Michigan
Title : Convolutional Neural Networks
Period : June 2020 - Present
Summary : E78WG79U6XYX, coursera.org, https://www.coursera.org/account/accomplishments/records/E78WG79U6XYX
Issuing Authority : DeepLearning.AI
Title : Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
Period : June 2020 - Present
Summary : FU796X48RBZU, coursera.org, https://www.coursera.org/account/accomplishments/records/FU796X48RBZU
Issuing Authority : DeepLearning.AI
Title : Neural Networks and Deep Learning
Period : May 2020 - Present
Summary : 7GFZAKTMTMEW, coursera.org, https://www.coursera.org/account/accomplishments/records/7GFZAKTMTMEW
Issuing Authority : DeepLearning.AI
Title : Structuring Machine Learning Projects
Period : May 2020 - Present
Summary : SNXHRBZ37L5S, coursera.org, https://www.coursera.org/account/accomplishments/records/SNXHRBZ37L5S
Issuing Authority : DeepLearning.AI
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