Experience


Machine Learning Engineer Intern

Spotify | Deep Learning for 173M user-trend analysis

  • Led data handling, analysis, deep learning design and productionization of seq-to-seq model for time-series analysis of 173 million Spotify users.
  • Achieved 10-20% Qini AUC, improving 50% over existing 6-7% XGBoost production model.
  • Led the end-to-end lifecycle, from data creation in BigQuery, data preprocessing and analysis, model design in TensorFlow / PyTorch, training on Vertex AI, test using PR-AUCs and Qini curve AUCs, model deployment to production pipelines in Kubeflow.
  • Deployed models to production pipelines with Kubeflow, Docker and Google Cloud Platform.
Jun 2022 - Aug 2022
New York, NY

Machine Learning Engineer Intern

Panoskin | Computer Vision Research and Development

  • Led the development end-to-end XGBoost and RandomForest pipelines with 91% precision, accuracy: for creating reliable 3D Google Map tours from 360 images, IMUs, Google Map APIs.
  • Modelled the pipeline end-to-end to extract data from computer vision data, create features from the data, search best features, train and test models for confidence predictions on 3D image data.
  • Working on machine learning for improving 360 image based google map tours.
Apr 2022 - Jun 2022
Chicago, IL (Remote)

Machine Learning Research Assistant

Computer Science Department, Carnegie Mellon University | Deep learning research

  • Published a conference paper with the EAAI symposium as part of the AAAI 2022, The paper can be found here.
  • Developing word-embedding visualization software for explainable natural language processing.
  • The software is deployed at a national level for setting AI guidelines and teaching AI in schools in Georgia.
Sep 2021 - Present
Pittsburgh, PA

Machine Learning Instructor

Inspirit AI | AI innovators - graduate program mentorship

  • Led a team of 10 undergraduate, graduate students to build a music recommender system project on Spotify data APIs using content filtering, applying BERT embeddings to audio datasets and music data.
  • Led a series of machine learning lectures from basics to deep learning applications in vision and language models using appropriate neural network architectures.
  • Conducted a professional development session for networking and working with the machine learning industry.
Dec 2021
Palo Alto, CA (Remote)

Deep Learning Research Fellow

College of Engineering, Carnegie Mellon University | Deep Learning Research

  • Designed a TensorFlow based neural network solver for solving flow problems with computational efficiency.
  • Optimized the physics informed neural network to generate accurate predictions using tailored loss functions using gradients extracted from backpropagation and autograd functionalities of TensorFlow.
Jun 2021 - Aug 2021
Pittsburgh, PA

Computer Vision Research Student

CERLAB, Carnegie Mellon University | Computer vision research

  • Used convolutional neural networks in conjunction with geometrical algorithms for 3D pose estimation in UAV quadrotor.
  • Performed 3D bounding box detection using YOLOv3 for navigation of the quadrotor.
Jan 2021 - Jun 2021
Pittsburgh, PA

Machine Learning Instructor

Camp K12 Inc. | Machine Learning program mentorship

  • Taught around 100 students machine learning basics using JavaScript
  • Mentored image, video, sound detection projects, chatbots and 3D interactive apps.
  • Projects were created using JavaScript, Google Teachable Machine, ml5, p5 libraries, proprietary and open source JS based platforms
Sep 2018 - Jan 2019
Mumbai, India

Design & Controls Engineer

PMV Electric Pvt. Ltd. | Electric vehicle engineering

  • Modelled the cruise control system for a battery electric vehicle by programming a PID controller
  • Initially simulated a dynamic vehicle model with basic manual vehicle controls.
  • The model was deployed on a Carla server and tested on a simulated vehicle.
  • Finally the programmed controller logic was deployed and tested on a C++ based Curtis EV controller.
  • Also designed and optimized body frame of the vehicle using ANSYS and SolidWorks based crash simulations to get a 51.38% weight reduction
  • Vehicle completed 600 km of successful testing based on these designs. You can see the launched product here.
Jun 2018 - Sep 2020
Mumbai, India

Project Department Intern

Mahindra and Mahindra Limited | new launches

  • Worked on an upcoming vehicle prototype, now launched as the Mahindra Marazzo
  • Created solutions to 107 different fouling problems using electro-mechanical engineering techniques.
Jun 2017 - Jul 2017, Jun 2016 - Jul 2016
Mumbai / Nashik, India