Abishek Ahluwalia

Machine Learning Engineer

Hyderabad, Telangana, India10 yrs 11 mos experience
Highly StableAI Enabled

Key Highlights

  • 10 years of experience in machine learning and data science.
  • Expertise in NLP and generative AI solutions.
  • Proven track record in building impactful end-to-end solutions.
Stackforce AI infers this person is a Machine Learning Engineer with expertise in NLP and SaaS product development.

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Skills

Core Skills

Machine LearningNatural Language Processing (nlp)Data Science

Other Skills

AlgorithmsAndroidAndroid DevelopmentApplied Machine LearningCC++CSSCocos2dComputer VisionCore JavaData AnalysisData ModelingData StructuresDatabasesDeep Learning

About

Senior Machine Learning Software Engineer specializing in NLP, GenAI, and Deep Learning (previously at Google). I have 10 yrs of experience in Machine learning and Data science, building impactful products and end-to-end solutions, as well as tackling diverse business use cases and challenges at companies ranging from seed-stage start-ups to well-established Series C organizations. My experience encompasses building and deploying services for applications like online clustering user issues extracted using LLM from support cases/transcripts to generate aggregated dashboards of real time trends Google, and previously customer churn prediction, chat classification and product attribute extraction. I have a strong academic background in computer science with a B.Tech in Computer Science and Engineering from IIT Guwahati and a research internship at Carnegie Mellon University . I'm passionate about leveraging the potential of AI to solve real-world problems and unlock new possibilities made feasible by rapid advancements in the field, ultimately leading to tangible improvements in customer experiences and user journeys .

Experience

10 yrs 11 mos
Total Experience
1 yr 6 mos
Average Tenure
--
Current Experience

Google

Senior Machine Learning Engineer

Oct 2023Apr 2025 · 1 yr 6 mos · Hyderabad, Telangana, India · On-site

  • To enable clients to identify top and trending user issues within vast datasets of transcripts and support cases, dynamically in real time. I designed a streaming topic clustering solution through iterative experimentation. I leveraged and optimized LLMs, embeddings and online clustering algorithms.
  • Led the design and productionization of an end-to-end Inferencing architecture, resulting in a scalable, configurable service for clients.
Natural Language Processing (NLP)Large Language Models (LLM)Deep LearningModel DevelopmentMachine Learning

Healthifyme

Senior Machine Learning Engineer

Jul 2021Aug 2022 · 1 yr 1 mo

  • Built Prediction Models for Customer Churn and Customer Chat Classification to retain and target customers more effectively.
  • Led discussions with various stakeholders using data driven insights to evolve and define precise problem statements more in line with businesses’ needs.
StatisticsMathematicsKey MetricsMachine LearningData Science

Clustrdata

Data Scientist II

Mar 2017Jun 2021 · 4 yrs 3 mos · Bengaluru Area, India

  • I built a product attribute extraction engine using biltsms to resolve stock keeping units and enrich the reference entity graph to reflect dynamically changing markets.
  • I also developed an approach for removing the ambiguity and establishing the confidence in the resolution/mapping of customer stock keeping units to our catalogue.
StatisticsTensorFlowMathematicsKey MetricsData ScienceMachine Learning

Stayzilla

Data Scientist II

Nov 2016Feb 2017 · 3 mos · Bengaluru Area, India

  • I worked with luigi and spark to handle large datasets using map reduce and R/python to do exploratory and machine learning analysis and gain insights visualized using metabase , based on which key business decisions are taken .
  • I also worked on demand forecasting .
StatisticsMathematicsKey MetricsData Science

Elementora

Senior Python and ML developer

Apr 2016Nov 2016 · 7 mos · Bengaluru Area, India

  • I worked with python backend , google app engine and angular.js to discover meta intelligence about user's preferences , needs , requirements , relationships and goals from mobile datasets for ele ( user's personal ai advisor ) to enrich his daily life journey by generating time, money and joy value for him .

Ideaphora inc.

Analytics Engineer

Aug 2015Jan 2016 · 5 mos · Bengaluru Area, India

  • At Ideaphora Inc. I have used Clearnlp , Google Semantic Vectors , LexPage Rank and NLTK to extract keyphrases and semantic /grammatical tuples to develop concept maps for the students.

Strand life sciences

Associate Software Developer

Aug 2012Jun 2015 · 2 yrs 10 mos · Bangalore

  • Worked on various hierarchical clustering algorithms, statistical models like Principal Component Analysis, Partial Least Square discrimination class prediction algorithm and variants along with diagnostic metrics such as R^2 Q^2, Permutation tests and 2-D 3-D graphical visualizations of t^2 hotelling’s confidence ellipses. Also worked on a web based visualization of elastic genome browser.

Carnegie mellon university

Research Intern

Jul 2012Aug 2012 · 1 mo · Greater Pittsburgh Area

  • Customized Constraint Based Indoor Path Planning for Handicap Users on Smartphones:-
  • Purpose -Adapting grid path planning according to various constraints such as user constraints (size constraints for wheelchair bound users, structural support constraints of visually handicap and instruction constraints.) and localization constraints.
  • Features:- Localization using WIFI and GSM Signal Strength Mapping along with available onboard sensors like accelerometer, magnetometer and Gyroscope gives the user’s exact location on the map. Path Planning is done with implementing Dstar algorithm. Various constraint problems are addressed by modifying cost matrices dynamically according to user handicap and optimizing them using linear programming. For example for visually handicap no. of breaks in the structure beside the path, unused doors on the way, hand preference and orientation are also accounted for. The cost matrix for the map is initialized with a cost proportional to the distance to closest wall as they tend to walk along a structure(wall, fence etc)
MathematicsData Science

Zunaa software pvt ltd

Intern

May 2011Jul 2011 · 2 mos · Bangalore

  • RUSH DEFENSE – an ios application for a tower defense game for ipad
  • All the bullet collisions and player enemy collisions were handled using chipmunk physics engine with cocos 2D . It has shades of a traditional tower defense game, as the user has to protect a HOMEBASE, from various waves of different kinds of ENEMY ALIENS originating from different spawn points. Every character (enemy/troop) on colliding with any other character/ defense buildings dies instantly. Any bullet collision reduces the target’s hit -points. There are nine defense buildings broadly divided into 3 categories STRUCTURAL, SUPPORT, TROOP . they have different upgrades There is another HUD layer on the to display all the gameplay information .
Mathematics

Dalian maritime university

Research Intern

May 2010Jul 2010 · 2 mos · Dalian, Liaoning, China

  • Android-Based Library Way Finding Application : -
  • This application provides the mobile user with the location, shortest path and the directions to follow that path .The app is modeled and implemented on the institute library of Dalian Maritime University. It takes the name of the of the book and the author as the user input, finds the book’s location from the database and gives the desired output on the map.

Education

Carnegie Mellon University

Research intern — Robotics

Jan 2012Jan 2012

Indian Institute of Technology, Guwahati

Bachelor of Technology (B.Tech.) — Computer Science

Jan 2008Jan 2012

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