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Generative AI @ IBM Labs | ML | NLU | Chatbots | Product
Machine learning and NLP engineer with more than 7 years of relevant experience. 5+ years of experience in Conversational AI. I have worked across a variety of problems, use cases, and domains, especially in building machine learning algorithms for modeling text data. My work has revolved around leading small to medium teams and architecting end-to-end ML-driven solutions in products/platforms and getting them live into production. I have mostly worked in Python for analytics and deriving insights and building scalable models based on those. Previously worked on Java and iOS(Swift) for developing web and mobile applications.
Indraprastha Institute of Information Technology, Delhi
Master’s Degree, Computer Engineering
January 1, 2014 – January 1, 2016
Guru Gobind Singh Indraprastha University
Master of Computer Applications (M.C.A.), Computer Science
January 1, 2009 – January 1, 2012
Ramjas School, RK Puram
High School
January 1, 1993 – January 1, 2006
IBM
Software Development Manager
May 1, 2025 – Present
Bengaluru, Karnataka, India
IBM
Advisory Software Engineer
December 1, 2023 – Present
Bengaluru, Karnataka, India
Quantiphi
Associate Technical Architect - Machine Learning
July 1, 2021 – November 1, 2023
Google - Contract
Conversational AI Architect
August 1, 2020 – July 1, 2021
Bengaluru, Karnataka, India
Quantiphi
Senior Machine Learning Engineer
February 1, 2019 – July 1, 2021
Wysa
AI Engineer
December 1, 2016 – January 1, 2019
Bengaluru, Karnataka, India
doodleblue Innovations
iOS Architect
June 1, 2016 – November 1, 2016
Greater Chennai Area
Accenture
Research Intern - Accenture Technology Labs
January 1, 2015 – June 1, 2015
Bengaluru, Karnataka, India
IIIT-Delhi
Teaching Assistant
August 1, 2014 – July 1, 2016
India
National Informatics Center
Programmer
March 1, 2012 – December 1, 2013
India
Spatio Temporal Information Retrieval
February 1, 2016 – April 1, 2016
Built an android application that ranks results of a query according to the location from and time at which it is being fired. Lucene is used for building the index and searching. Initial index is built upon the spatial and temporal tags of the data corpus. New york times annotated data corpus with over 1.8 million articles, collected over a period of 20 years was used.
Location prediction for new resource
October 1, 2015 – April 1, 2016
A theoretical and mathematical spatial computing research project. The aim of the project was to predict a location in a spatial network for a new resource such as a petrol pump, hospital or school. The algorithm takes into account existing resources of the same nature within a geographical area, follows a helical search space and comes up with a new location so that maximum population benefits from the new resource and overall load on the resources of the region goes down.
Diabetic Retinopathy Detection
September 1, 2015 – November 1, 2015
Applied various image analysis and machine learning techniques on a huge corpus of high-resolution human retinal images to predict whether a patient suffered from diabetes or not. Some of the techniques used were vascular segmentation, HOG for feature vectors, SVM, SMOTE and ADASYN for handling the large bias. Final reported accuracy - 94.97
Photobucket
September 1, 2015 – November 1, 2015
A complete photo editing android application with the additional feature of age and gender detection. All features of a professional photo editing application such as image adjustments (brightness, contrast, sharpness, hue etc), various pre-defined filters for giving effects and collage templates were present. Application also had the ability to recognize human faces in an image and predict their age and gender with high accuracy.
Software Intelligence
January 1, 2015 – June 1, 2015
Researched, developed and laid foundations for the novel concept of software intelligence. The aim of the project is to provide intelligence into the software development lifecycle at various stages. Intelligence constitutes of information about the health of a project, whether it will meet timelines or not, what potential problems can crop up in the future etc. During the course of the internship, we worked on one module dealing with post-release phase of an application wherein our software would analyze how well an application is being received and what might be the possible causes for good/bad reviews Keywords: Software engineering, Named entity recognition, Sentiment analysis
Web applications for government organizations
March 1, 2012 – December 1, 2013
Developed various web applications such as online application portal, typing software with auto-correction and complete websites for various government organizations such as SSC, Supreme court, IBPS and WBSSC. Worked on GWT, SmartGWT and core java. PostgreSql in the backend.
Natural Language Processing with Classification and Vector Spaces
Coursera
June 24, 2026 – Present
NVIDIA DLI Certificate – Fundamentals of Accelerated Data Science with RAPIDS
NVIDIA
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse project background, ranging from theoretical spatial computing to practical web applications and advanced AI systems. Their experience spans various companies, including IBM, Quantiphi, Google (contract), and Wysa, indicating adaptability to different organizational cultures. The progression from programmer to manager and architect roles, coupled with a focus on AI/ML, aligns well with a growth-oriented and technically driven environment. The breadth of skills, from core Java to modern ML frameworks, suggests a continuous learning mindset. However, the lack of specific open-source contributions or community involvement in the provided data makes it difficult to fully assess collaborative cultural fit beyond professional team settings.
Soft Skills & Operational Fit
The candidate's experience as a Software Development Manager and AI lead suggests strong leadership, project management, and client interaction skills. Their work on conversational AI platforms implies an ability to understand user needs and translate them into technical solutions. The teaching assistant role also indicates good communication and mentoring abilities. The diverse project portfolio suggests adaptability and a problem-solving mindset.