Jul 2021 – Jan 2022 · 6 mos · Gurugram, Haryana, India

• ● Managing a team of 11 highly creative backend developers
• ● Started as Principal Engineer, got promoted officially in July, 2021
• ● Building, maintaining winning teams, including the next generation of leaders
• ● Planning individuals’ growth, keeping all motivated for better team health and velocity
• ● Managing and prioritising technical debts for different micro-services across trains' backend team
• ● Engaging decision-makers, devising winning strategies/solutions, and managing agility in the requirements
• ● Roles and responsibility of any individual contributor including coding, writing junits etc. and also acts as fallback.

Dec 2020 – Jun 2021 · 6 mos · Gurugram, Haryana, India

Dec 2020 – Dec 2021 · 1 yr

• SubEntity of IEEE: IEEE Transactions on Neural Networks and Learning Systems
• Publons Profile:
• https://publons.com/researcher/4173223/amandeep/
• Two research papers were reviewed so far:
• > "New Insights into Drug Repurposing for COVID-19 using Deep Learning"
• > "Deep learning of social media for predicting the temporal spread of COVID-19"

Jan 2020 – Jun 2021 · 1 yr 5 mos · India

• Authored a book titled "Implement NLP use-cases using BERT":
• https://www.amazon.com/dp/B092TN9N1V/ref=sr_1_1?dchild=1&keywords=Implement+NLP+use-cases+using+BERT&qid=1618807887&sr=8-1
• https://www.amazon.in/dp/9390684625/ref=sr_1_1?dchild=1&keywords=Implement+NLP+use-cases+using+BERT+bpb&qid=1618807871&s=books&sr=1-1
• Reviewed following books:
• https://www.amazon.in/dp/B09MS4SH59/ref=sr_1_1?keywords=Software+Design+Patterns+for+Java+Developers+bpb&qid=1638269585&sr=8-1

Oct 2018 – Dec 2020 · 2 yrs 2 mos · Gurugram, Haryana, India

• Industrialized / Pilot Projects: (primarily working in OSS department of Orange)
• 1. Service Insights for Incidents: [Java + Python]
• >> Intelligent service operations solution for emails’ management.
• >> Features: ((projected to handle more than 500 * 500 requests per day))
• >> Polling emails from exchange server with proper exception handling
• >> Text Classification : Critical (Negative), Urgent, , Positive, Neutral classes
• >> Insights dashboard showing customer satisfaction score, segregation percentages of emails, top 5 users affecting the overall customer satisfaction.
• >> Configurable alerting mechanism to notify urgent/critical emails
• 2. Data Quality Improvement: [Python]
• >> End-to-end reporting of service operations incidents
• >> Features: ((handling (50 to 70) * (200 to 1000) requests per day))
• >> Extraction of reports from existing reporting application
• >> Classification for severity and responsible party and machine translation for paraphrasing reason for outage.
• >> Email notifications for different stages of processing of requested reports post reconciliation.
• 3. Email-Bot for carrier management: [Java + Python + Scala(just tried for ML model)]
• >> Information Extraction from 250+ email templates
• >> Features: ((handling (100 to 242) * (5 to 20) requests per day))
• >> Integration of a new intelligent component with existing Java application.
• >> Extraction of meaningful information from unstructured data: Reference Id, carrier ids, start time, end time, reason for outage, impact duration, etcetera with re pipelines for 80% volume of emails and for the rest tried NER models have been trained using Spark-NLP library with Scala language.
• >> Connectors of two components have also been implemented.

Sep 2015 – Oct 2018 · 3 yrs 1 mo · Gurgaon, Haryana, India

• Project #1: RPA Innovations
• Description:
• This project is started to transform all business processes within ‘Natwest Markets’ business Units within RBS Group into efficient bots. Currently this project is over and above my current delivery of collateral management project.
• We kick started with a client on-boarding application where we receive scanned documents from our clients which need to be key-in our system after reconciliation of relevant data from different internal systems.
• ‘ML Engineers’ has the responsibilities for solving complex problems related to Machine Learning and artificial intelligence which are not given out of box in RPA vendor tools like OCR-integration (not supported till now in UI Path, but they now have integration Abbyy Flexi Capture which they would be releasing soon).
• It also takes care of finding all use-cases within ‘Natwest Markets’ which should be implemented using machine learning.
• Training other internal resources across RBS Group, India to leverage machine learning knowledge to increase our productivity and enhancing our customer experience to meet our 2020 goal  Customer satisfaction.
• Project #2: Collateral Management System
• Description:
• This project is started to implement new regulations in collateral management.
• In order to have only one application for entire collateral management, this project includes all necessary work to decommission old application and all features to support new regulation as defined by various regulatory bodies particularly
• in UK and US.
• Apart from application analysis, prediction models for dispute amount and categorisation of dispute reason were also implemented by leveraging a 90 days sliding window.

Mar 2015 – Sep 2015 · 6 mos

May 2014 – Sep 2015 · 1 yr 4 mos

• Implements User Stories.
• Investigates and resolves environment issues, if possible and provides necessary communications regarding progress, systems performance, issues and risks.
• Develop Junits for unit testing of various APIs.
• Code refactoring for improving Sonar Reports.
• Mentor Junior members of the our team, provides basics of domain for start-up.
• Provide suggestion to change the current process for making it the best.
• Discussion with QA resources for defect tracking on FT environments.

Jun 2012 – May 2014 · 1 yr 11 mos

• 1. Performs development/testing(Unit-testing) activities as directed by the Lead and Manager.
• 2. Monitors development environment and reliability; investigates and resolves issues, if possible and provides necessary communications regarding progress, systems performance, issues and risks.
• 3. Mentor Junior members of the our team, provides basics of domain for start-up.
• 4. Provide suggestion to change the current process for making it the best.
• 5. Initiating meetings with QA (Bug Dance) for defect tracking and prioritizing critical defects.
• 6. Coordination between onsite and offshore teams.
• 7. Daily Status reporting for any CR(closing, logging, KT requirement) and other issues to Team Lead as well as client, if necessary.

Jun 2011 – Apr 2012 · 10 mos · India

• ION initiative