Hey, I'm Ambesh.

I'm an ML engineer, passionate about research works and developing new skills.


I'm a currently an ML engineer at Hike India. I completed my undergraduate degree with majors in Computer Science and Engineering from Birla Institute of Technology Mesra, Patna. I have worked in related fields like machine learning, artificial intelligence, software engineering, internet of things and data mining. I strive to contribute in machine learning fields as the concept and large applicabilty of machine learning fascinates my curious mind and provides a space to come up with my own ideas.

"Growth occurs when one goes beyond one's limit. Realizing that is also a part of the training."
I enjoy learning new and keep moving forward so that I could acquire as much as I could get. I consider work as an ongoing process, and I'm always looking for opportunities to work with those who are willing to share their knowledge. At the end of the day, my primary goal is to work hard and gather knowledge.

When I'm not in front of a computer screen, I'm probably reading books, thinking about robotics, playing football, reading mangas, or cooking.

What I Do


Completed my bachelor's engineering course from Birla Institute of Technology, Mesra. Solving daily problems through my skills and experience.

Machine Learning

Practicing machine learning and data science. Getting my hands dirty on kaggle dataset and understanding methods proposed by researchers in their work.


I practice my coding on various platforms and compete with my friends. I use this quirk to help others by guiding them or helping them in their work.


I was a former secretary, technical support and one of the people who established the Technical Club at Birla Institute of Technology aiming to provide a platform for students intrigued by the concepts of machine learning and IoT and to make them aware of the current working ambience in this field by encouraging them to take part in different competitions and research.



  • Python
  • C/C++
  • Java
  • JavaScript
  • Tensorflow
  • Pytorch
  • Blender
  • Unity
  • Raspbian


  • checkmarkGit + Github
  • checkmarkUnix Commands
  • checkmarkPyCharm
  • checkmarkArduino
  • checkmarkArduPilot
  • checkmarkOverLeaf


  • checkmarkProgramming
  • checkmarkMachine Learning
  • checkmarkResearch
  • checkmarkRobotics
  • checkmarkDesigning


Thanks to my college, I was able to get deeper insights into the fields of my interest and was able to undertake research in machine learning.

ML Engineer


Machine learning engineer, working on speech technologies and their applications in deep learning.

December 2021 - Present

ML Intern


Machine learning engineer intern, implementing machine learning models and learning different approaches to solve business problems. Coordinating with team, and managing project development.

September 2021 - November 2021

Undergraduate Student

Birla institute of Technology, Mesra

Candidate for Bachelor of Engineering in Computer Science & Engineering with a concentration in Machine learning and a minor in Robotics. Graduating in Spring 2021.

2017 - 2021

Research Intern


Working under Researcher Natalia Díaz Rodríguez on analyzing parisitic images to classify their taxonomy.

February 2021 - Present

Research Assistant

Birla institute of Technology, Mesra

Assisted a computer science Professor in the development of a research paper by implementing it and testing the code on the given data to provide analysis and results. Published two papers in IEEE BigMM and ICCCS2020. Developed remotely to meet weekly deadlines and project checkpoints during the pandemic.

January 2020 - May 2020


Technical Club: Electronics and Communication

Was one of the founding members and led projects on machine learning, IoT and robotics that were held by it. As a secretary organized a number of workshops for the benefits of the members as well as the interested. Helped them to understand the matters of IoT and machine learning betterly.

October 2019 - August 2020

Project Assistant

Laboratoire d'Informatique de Grenoble

Assist in development and programming algorithms. Extract and clean the data along with provide statistical solutions to deal with them. Design neural network architecture to solve problems related to Natural language processing.

June 2020 - July 2020
View my full résumé view resume

Some of My Work

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Automated Medical Assistance is my research, where we developed a conversational dialogue system that is able to provide better consultation during the need and is able to answer any queries related to one’s health.

  • BERT
  • GPT2
  • BART
  • Hugging Face-Transformers
  • Pytorch
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Analysis of Resource-efficient Predictive Models for Natural Language Processing

In this paper, we presented an analyses of the resource efficient predictive models, present in the machine learning field for resource constraint devices. These models try to minimize resource requirements like RAM and storage without hurting the accuracy much. We utilized these models on multiple benchmark natural language processing tasks, which were sentimental analysis, spam message detection, emotion analysis and fake news classification.

  • Binary Neighbor Compression
  • Random Forest
  • SVM
  • Naive Bayes
  • ProtoNN
  • Bonsai Tree
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Character Level Pretrained Language Model for Extracting Support Phrases for Sentiment Labels

A novel character-level pretrained language model framework which utilizes the transformers and character-level language models to extract sentiment phrases.

  • Hugging Face-Transformers
  • Char-level Transformers
  • RNN
  • CNN
  • WaveNet
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MemSem is a multi-modal framework for sentimental analysis of memes. With the help of multi modal architecture it extract features from the input to provide a meaningful analysis for a meme, whether its offensive, humorous or non-sense. The project is published in IEEE BigMM 2020 Publications and is still in progress.

  • Tensorflow
  • Hugging Face transformer
  • Python Reddit API Wrapper
  • google-images-downloader
  • NLTK
  • Pytessaract
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QuesBELM is a natural question answering system, based on natural language processing and ensemble methods. It works on an ensemble model of BERT-base, Albert-xxl and BERT-large. Trained on SQuad2.0 dataset, preprocessed and sampled to provide better results. It produces outstanding results and is helpful for researches related to natural question answering.

  • Pytorch
  • Hugging Face transformer
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ASL-Classifier is a python wrapper object. It's a real-time based classifier, helps in detecting and classifying American Sign language. With the help of Haarscascade and opencv it detects palm in the view and uses pretrained keras model in classification. It uses opencv library to create window applications to manage settings and classify output.

  • Keras
  • OpenCV
  • Haarscascade
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Tweeple DNA is a FastAPI based project that classifies twitter-people's account into bot or human, as well as assigns probabilty for being a bot ranging from 0-1.

  • zlib
  • XGBoost
  • lightGBM
  • tweepy
  • FastAPI
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hiLyted is a project which clips highlights of video. It is based on the method of short time energy in audios extracted from a video. It captures the time period containing high pitch sound considering it as audience applause during the tournament. It downloads the video and audio from youtube using youtube-dl and extracts audio feature using Librosa, with the help of MoviePy it clips the time period of the highlights and saves it in a local directory.

  • Youtube-dl
  • Librosa
  • MoviePy
  • Python
See more projects github

Get In Touch

Want to work with me and solve worldly problems or just want to say hi? Feel free to send me a message!