Rishab Pal, Developer in Bengaluru, Karnataka, India
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Rishab Pal

Verified Expert  in Engineering

Data Scientist and AI Developer

Location
Bengaluru, Karnataka, India
Toptal Member Since
November 10, 2022

Rishab is an experienced data scientist and machine learning (ML) expert with a strong passion for mathematics and artificial intelligence (AI). He has 6+ years of experience designing and developing end-to-end machine learning solutions that have been successfully deployed to production on cloud platforms. Rishab constantly invests in his skills to stay up-to-date with the latest advancements in the field. He is committed to applying his knowledge and expertise to develop impactful solutions.

Portfolio

Nolea Technology Ltd
Python, Scikit-learn, Pandas, Amazon Web Services (AWS)...
Revibe AI
Generative Pre-trained Transformers (GPT), Python, Chatbot Conversation Design...
Zachary Gidwitz
Data Science, Machine Learning, Python, Recommendation Systems, Data Strategy...

Experience

Availability

Part-time

Preferred Environment

Machine Learning, Deep Learning, Data Science, Natural Language Processing (NLP), Computer Vision, Python, Artificial Intelligence (AI), Generative Artificial Intelligence (GenAI), Machine Learning Operations (MLOps)

The most amazing...

...accomplishment I've had was showcasing my project at CES—International Consumer Electronics Show, the technology sector's flagship trade fair, in 2019.

Work Experience

AI/ML Expert

2023 - 2024
Nolea Technology Ltd
  • Built an MVP for the recommendation system to match healthcare companies with clinical specialists in mental healthcare, allied healthcare, orthopedics, etc.
  • Re-engineered the existing recommendation engine using SOTA NLP approaches and machine learning models like NER, LayoutLM, and LayoutParser, and built custom doc embeddings.
  • Designed a cloud-native trainable and scalable architecture, previously built on a rule engine that lacked robustness for their business model.
Technologies: Python, Scikit-learn, Pandas, Amazon Web Services (AWS), Artificial Intelligence (AI), Machine Learning, Recommendation Systems, Retrieval-augmented Generation (RAG), Generative AI, Azure AI Studio

LLM Chatbot Developer

2023 - 2023
Revibe AI
  • Completed a POC of a mental health assistant built on top of Voiceflow. It understands the user's mind, responds with appropriate custom suggestions from the given knowledge base, or engages in a general conversation like a human.
  • Built the RAG-based chatbot that replicates the behavior of a neuroscientist and emphatically engages with the user during the conversation.
  • Used LangChain to enrich the vector store, adding proprietary neuroscience and psychological data to generate a more relevant response from the LLMs.
Technologies: Generative Pre-trained Transformers (GPT), Python, Chatbot Conversation Design, API Integration, Natural Language Understanding (NLU), Natural Language Processing (NLP), Language Models, Artificial Intelligence (AI), Voiceflow, Cognitive Behavioral Therapy (CBT), Zapier, Machine Learning, Chatbots, Retrieval-augmented Generation (RAG), Generative AI, Azure AI Studio, LangChain, Integrated Development Environments (IDE)

ML Expert | Data Scientist

2023 - 2023
Zachary Gidwitz
  • Built a recommendation engine for an addiction recovery app that incorporates user demographics, mental state, and other metadata from app interaction to suggest quotes and prayers relevant to the user's state of mind.
  • Fine-tuned the OpenAI GPT3 model and used Langchain to build a sequence of prompts where each preceding answer is included in the subsequent question. I added memory and linked the vector database quickly.
  • Provided several offline and online metrics to track the live performance of the model and the recommendation system.
Technologies: Data Science, Machine Learning, Python, Recommendation Systems, Data Strategy, Data, Chatbots, OpenAI GPT-3 API, Jupyter, Cloud, OpenAI GPT-4 API, Chatbot Conversation Design, Integration, Programming, AI Programming, Data Cleaning, Unstructured Data Analysis, Airtable, Machine Learning Automation, Project Management, Statistical Analysis, Data Reporting, Data Cleansing, Prompt Engineering, Retrieval-augmented Generation (RAG), Generative AI, Azure AI Studio, LangChain

Machine Learning Engineer

2023 - 2023
Odem Global Pty Ltd
  • Trained causal language model (CLM) with DeepSpeed on Bittensor, a peer-to-peer open-source protocol powering a globally distributed decentralized neural network.
  • Used a mountain dataset (800+ GB) to train generative LLMs using DeepSpeed, which has lower network validation loss and thereby increases the model's reward, benefiting the client.
  • Contributed to hyper-parameter tuning and revamped the default PyTorch data loader for faster dataset loading. Also, validated the models' performance on the validation set to ensure it meets the desired performance metrics.
  • Fine-tuned models like GPT-J-Neo, Llama, MPT, Vicuna, Koala, Cerebras, to mention a few.
Technologies: Language Models, Machine Learning, Fine-tuning, Causal Inference, DeepSpeed, OpenAI GPT-3 API, Jupyter, Cloud, Integration, Programming, AI Programming, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Large Language Models (LLMs), Project Management, Regex, Statistical Analysis, Data Reporting, Data Cleansing, Prompt Engineering, Chatbots, Retrieval-augmented Generation (RAG)

AI Expert

2023 - 2023
Rich Lemon Apps FZE LLC
  • Developed a user sticker model using Stable Diffusion and ControlNet for a given style.
  • Experimented with different configurations of parameters to understand the effect on the results and achieved state-of-the-art results.
  • Explored different methods like checkpoint merging, trained a stickers model, and then fine-tuned that model on Portrait Face, and combined sticker style and user image training.
Technologies: Artificial Intelligence (AI), Deep Learning, Image Processing, Stable Diffusion, Computer Vision, ControlNet, 3D, Microservices Architecture, Data Scientist, Jupyter, Cloud, Integration, Programming, AI Programming, Data Cleaning, Machine Learning Automation, Image Analysis, Project Management, Statistical Analysis, Data Reporting, Data Cleansing, Prompt Engineering, Image Generation, Text to Image, Multimodal GenAI

Senior ML Expert | Data Scientist

2021 - 2023
EagleView
  • Revamped roof measurement automation for US houses by engineering a high-performance Line Detection model on aerial imagery to detect roof, wall, and ground lines from 28% to 59%.
  • Developed segmentation models for roof and wall facet detection while handling obstruction, achieving 86% accuracy.
  • Improvised complex PyTorch models to facilitate ONNX and TensorRT export for efficient deployment using NVIDIA Triton Server.
  • Orchestrated microservices using Step Functions, AWS Lambda, and Amazon SageMaker endpoints, improving response time by 25%. This was followed by simplifying maintenance and support, focusing on maximizing code reuse.
Technologies: Python, Machine Learning Operations (MLOps), PyTorch, Python API, Docker, Computer Vision, GPU Computing, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Data Science, SQL, Neural Networks, Data Visualization, Unsupervised Learning, Code Review, Remote Team Leadership, Graphics Processing Unit (GPU), Transfer Learning, Transformers, Sequence Models, Image Retrieval, Image Recognition, Classification, Entity Extraction, Siamese Neural Networks, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), TensorBoard, Generative Adversarial Networks (GANs), Linux, Language Models, Python 3, Recommendation Systems, Algorithms, XGBoost, Data Extraction, Data Manipulation, Snowflake, Analytics, MySQL, Amazon Web Services (AWS), Data Analysis, Version Control Systems, Communication, Data Engineering, Regression, RAPIDS, APIs, Amazon SageMaker, NoSQL, Image Search, AI Design, Jupyter Notebook, Flask, NVIDIA TensorRT, Microservices Architecture, Data Scientist, Jupyter, Cloud, Anomaly Detection, Integration, Programming, AI Programming, Bitbucket, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Kubernetes, Amazon Elastic Container Service (Amazon ECS), Image Analysis, Large Language Models (LLMs), Project Management, Statistical Analysis, Data Reporting, Data Cleansing, You Only Look Once (YOLO)

Senior Software Engineer/Machine Learning (ML)

2020 - 2021
Airtel India
  • Designed and built a chatbot, leveraging HuggingFace transformers with DeepSpeed to resolve queries for over 400 million of Airtel's monthly active users. Deployed successfully, handling over 10 million daily conversations with 85% accuracy.
  • Improved the accuracy of face recognition, matching, and liveness-check models. Added face segmentation, blur and forgery detection, real-time blacklisting, and face search. Enhanced service efficiency and reduced manual effort by over 25%.
  • Inculcated best MLOps practices on the team to lower technical debt and adapt workflow that requires little to no manual intervention for simulations, testing, deployment, and monitoring.
Technologies: Data Analytics, Statistical Modeling, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Python 3, Docker, Bash Script, Data Science, SQL, OCR, Neural Networks, Optimization, Clustering, Code Review, Remote Team Leadership, Graphics Processing Unit (GPU), Transfer Learning, Transformers, Sequence Models, Image Retrieval, Image Recognition, Classification, Entity Extraction, Recurrent Neural Networks (RNNs), Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), TensorBoard, Generative Adversarial Networks (GANs), Topic Modeling, Linux, Language Models, PostgreSQL, Recommendation Systems, Algorithms, Generative Pre-trained Transformer 3 (GPT-3), XGBoost, Data Extraction, Data Manipulation, Snowflake, Analytics, MySQL, Amazon Web Services (AWS), Handwriting Recognition, Data Analysis, Version Control Systems, Communication, Data Engineering, Regression, RAPIDS, APIs, Amazon SageMaker, NoSQL, Image Search, Amazon Rekognition, AI Design, Jupyter Notebook, Flask, NVIDIA TensorRT, Microservices Architecture, Data Scientist, Chatbots, Jupyter, Cloud, Anomaly Detection, OpenAI GPT-4 API, Chatbot Conversation Design, Integration, Programming, AI Programming, Bitbucket, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Kubernetes, Amazon Elastic Container Service (Amazon ECS), Image Analysis, Large Language Models (LLMs), Project Management, Statistical Analysis, Data Reporting, Data Cleansing, Big Data

ML Engineer

2019 - 2020
Trantor Software
  • Designed and deployed an OCR solution that outperformed the accuracy of Google OCR by 12% as benchmarked on the ICDAR 2013 dataset. Reduced the overall cost from an estimated $1 million to less than $50,000 per year.
  • Prototyped a natural language processing (NLP)-based bot using recurrent neural networks to parse comments on the website, assess sentiments, and classify them into themes. Enabled standard responses and activation of the needed systems to respond.
  • Worked on a trained convolutional neural networks model using INT8 fixed-point arithmetic. Designed algorithms to decide the Q. Collaborated to enable classifiers, detectors, generative adversarial networks (GANs), and segmentation networks.
  • Trained a software categorization and brand recognition tool using word2vec, N-grams embeddings, and kNN classifier. This tool was capable of recognizing product titles and descriptions.
  • Managed quantization-aware training of convolutional neural networks and worked on fine-tuning and post-training quantization.
Technologies: Machine Learning, Deep Learning, Data Science, SQL, Artificial Intelligence (AI), OCR, Data Visualization, Optimization, Unsupervised Learning, Clustering, Code Review, Remote Team Leadership, Graphics Processing Unit (GPU), Transfer Learning, Transformers, Sequence Models, Image Recognition, Classification, Recurrent Neural Networks (RNNs), Siamese Neural Networks, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), TensorBoard, Generative Adversarial Networks (GANs), Topic Modeling, Linux, Language Models, Python 3, Recommendation Systems, Algorithms, Generative Pre-trained Transformer 3 (GPT-3), XGBoost, Data Extraction, Data Manipulation, Snowflake, Analytics, MySQL, Handwriting Recognition, Google Vision API, Data Analysis, Version Control Systems, Communication, Data Engineering, Regression, RAPIDS, APIs, Amazon SageMaker, NoSQL, Image Search, Amazon Rekognition, AI Design, Jupyter Notebook, Flask, Microservices Architecture, Data Scientist, Chatbots, Jupyter, Cloud, Google Cloud Platform (GCP), Anomaly Detection, OpenAI GPT-4 API, Chatbot Conversation Design, Integration, Programming, AI Programming, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Image Analysis, Large Language Models (LLMs), Project Management, Regex, Statistical Analysis, Data Reporting, Data Cleansing, You Only Look Once (YOLO), Elasticsearch

Software Engineer

2018 - 2019
Yamaha Motor Solutions
  • Conceptualized and built a ConvLSTM model on TensorFlow for hand gesture recognition. Used Bayesian optimization techniques for hyperparameter tuning.
  • Worked on single-shot face recognition using SSD MobileNet for detection and Inception-ResNet v2 for feature extraction. Introduced TP-GAN for photorealism and identity, preserving the frontal face-view synthesis from any pose.
  • Led a team to propose and implement predictive analysis for retail sales forecasting using ARIMA, exponential smoothing, and Holt's Winter models. This resulted in a 5.35% increase in quarterly sales.
  • Implemented conditional Wasserstein generative adversarial network (cWGANs) to synthesize new vehicle designs from given samples.
Technologies: Python 3, Machine Learning, Data Science, SQL, Artificial Intelligence (AI), Neural Networks, Data Visualization, Optimization, Code Review, Graphics Processing Unit (GPU), Transfer Learning, Machine Vision, Sequence Models, Classification, Siamese Neural Networks, Convolutional Neural Networks (CNN), Artificial Neural Networks (ANN), TensorBoard, Generative Adversarial Networks (GANs), Linux, Algorithms, XGBoost, Data Extraction, Data Manipulation, Snowflake, Analytics, MySQL, Handwriting Recognition, Data Analysis, Version Control Systems, Communication, Data Engineering, Regression, APIs, Amazon SageMaker, NoSQL, AI Design, Jupyter Notebook, Flask, Data Scientist, Jupyter, Cloud, Integration, Programming, AI Programming, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Image Analysis, Project Management, Regex, Statistical Analysis, Data Reporting, Data Cleansing, You Only Look Once (YOLO), Point Cloud Data, Point Clouds

Artificial Intelligence-based Document Capturing and Processing | AIDCAP

https://randomtrees.com/dcap
1. I fully automated the document capture and information extraction process using NLP and CV and it mainly dealt with invoices and orders from different sources, including emails, PDFs, DOCX, or images.

2. Built and trained custom models for region proposal and text recognition with enhanced semantic understanding using Transformer.

Search Relevance and Ranking

https://www.airtelxstream.in/
1. Improved Search Relevance and Ranking metrics like click-through rates (CTR), conversion rate, and ads revenue for organic and ads merchants at an eCommerce site.

2. I alternated search keyword generation, increasing ad revenue by 20%. The system is scaled to handle >2,000 RPS using a Milvus-based vector search and is automatically refreshed daily. I then worked on a semantic search.

3. A custom deep semantic matching model trained for matching search queries with products. This resulted in a 10% growth in ad revenue. I also worked on search query classification using custom-trained embeddings for query understanding to match the search query with product leaf categories.

4. This project improved CTR by 50%, leading to a 37% incremental uplift in revenue and a 17% decrease in discount utilization. I improved the CTR using machine learning (ML)-based learn-to-rank models starting from simple linear regression and tree-based models, such as LightGBM and XGboost. These were combined with deep models for search-query understanding.

Callup AI | Chatbot Platform

https://www.airtel.in/contact-us
1. A generative chatbot for user queries using a Transformer-based Seq2Seq model from chat messages. It is currently deployed commercially, handling thousands of daily conversations in English or Hinglish with almost 85% of accuracy.

2. It also comprised the nearest neighborhood-based intent detection solution using pre-tagged customer messages for tagging new customer messages to the support team.

3. The idea was to reduce customer service workload by automatically replying to user messages with pre-defined responses based on intent detection.

VirtualHR | Candidate Recommendation Engine

1. A tool to automate matching job descriptions with resumes, facilitating the process of getting top candidates out of thousands based on several parameters, namely experience, education, skillset, projects, location, etc., and providing a weighted similarity score based on input parameters.

2. I automated the end-to-end process, leveraging the state-of-the-art (SOTA) NLP and machine learning approaches with cloud deployment.

Retail Sale Forecasting

https://www.yamaha-motor-india.com/
1. Analyzed the sales trends and sizing curve distribution across categories and product lines to give recommendations on the localized sizing distribution for a demand forecast model.

2. I proposed and implemented a predictive analysis for biweekly retail sales forecasting using ARIMA, exponential smoothing, and Holt-Winter methods.

3. The next step was incorporating Bayesian hyperparameter tuning with hybrid modeling using principal component analysis, support vector machines, and ensemble learning methods with Random Forests and XGBoost. This led to a 10% year-on-year increase in key metrics such as sales revenue.

Churn Prediction

1. Initiated customer churn prediction in a subscription-based purchase model. The first use case was for a telecommunication provider, and the second was for a retail giant.

2. I leveraged, structured, and unstructured sales and customer information. This included chat, ratings, reviews, email, and voice chat transcripts for designing KPIs. The model could predict churn almost two weeks before it happened.

3. The next step was ideating and implementing an A/B test framework and SQL queries. The framework defined key metrics to analyze model performance statistical significance.

Virtual Try-on

https://vimeo.com/476518018
1. A real-time apparel-based virtual try-on using a cutting-edge complex ML pipeline. It provides a real-time, immersive, clothing-trial experience on a phone or kiosk with a single image and well-thought-out recommendations that will eventually help in more sales.

2. Increased in-store purchases by over 25% and via-app purchases by over 20%.

Face Dedupe Platform | Face Recognition, Matching, and Retrieval

https://www.airtel.in/bank/video-kyc
1. A platform with various microservices, including face recognition, face matching, and face liveness-check models.

2. I updated the platform with face segmentation, face blur detection, document forgery detection, real-time blacklisting, and face search to improve service efficiency and reduce manual effort by over 25%.

Price Optimization

https://tiki.vn/
1. Worked on optimization of prices of retail products for Tiki using demand prediction by ML models. I used time-series historical sales data; a LightGBM model is trained to predict sales at daily and three-day frequencies.

2. The work included data analysis, feature engineering, stakeholder management, designing A/B experiments, and performing statistical analysis for hypothesis testing.
2014 - 2018

Bachelor's Degree in Computer Science

DIT University - Dehradun, India

SEPTEMBER 2019 - PRESENT

Deep Learning Specialization

Coursera

MAY 2018 - PRESENT

Machine Learning

Coursera

APRIL 2018 - PRESENT

Big Data Modeling and Management Systems

Coursera

MARCH 2018 - PRESENT

Programming the Internet of Things (IoT) Specialization

Coursera

Libraries/APIs

TensorFlow, PyTorch, Python API, OpenCV, Scikit-learn, Pandas, NumPy, SciPy, Natural Language Toolkit (NLTK), SpaCy, XGBoost, RAPIDS, REST APIs, Google Vision API, Keras, Amazon Rekognition, DeepSpeech

Tools

TensorBoard, Amazon SageMaker, Jupyter, Bitbucket, You Only Look Once (YOLO), OpenAI Gym, ChatGPT, Amazon Elastic Container Service (Amazon ECS), Dialogflow, NGINX, GIS, CPLEX, Apache Airflow, AutoCAD, Zapier

Frameworks

Flask, Accelerate

Languages

Python, SQL, Python 3, Regex, Bash, Snowflake, JavaScript, Bash Script

Paradigms

Data Science, Siamese Neural Networks, ETL, Microservices Architecture, Automation, Anomaly Detection, Microservices

Platforms

Linux, Jupyter Notebook, Docker, Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Kubernetes, Mixpanel, Azure AI Studio, Blockchain, Voiceflow

Industry Expertise

Project Management

Storage

PostgreSQL, MySQL, NoSQL, Google Cloud, Elasticsearch

Other

Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Software Deployment, Software Design, Statistics, Statistical Modeling, Data Analytics, Machine Learning Operations (MLOps), Image Processing, BERT, Long Short-term Memory (LSTM), Predictive Modeling, Hugging Face, Artificial Intelligence (AI), OCR, Neural Networks, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNN), Artificial Neural Networks (ANN), Time Series Analysis, Entity Extraction, Classification, Image Recognition, Image Retrieval, Object Detection, Sequence Models, Machine Vision, Transformers, Transfer Learning, Graphics Processing Unit (GPU), Remote Team Leadership, Code Review, Generative Adversarial Networks (GANs), Clustering, Topic Modeling, Data Visualization, Mathematics, Optimization, Language Models, Recommendation Systems, Algorithms, Data Collection, Data Extraction, Data Manipulation, Large Data Sets, Analytics, Data Analysis, Models, Version Control Systems, Communication, Modeling, Data Engineering, Regression, APIs, Image Search, AI Design, Fine-tuning, Causal Inference, Data Scientist, Generative Pre-trained Transformers (GPT), Decision Trees, Chatbots, Cloud, OpenAI GPT-4 API, Chatbot Conversation Design, Integration, Programming, AI Programming, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Language Learning, Image Analysis, Large Language Models (LLMs), Statistical Analysis, Data Reporting, Data Cleansing, API Integration, Prompt Engineering, Image Generation, Text to Image, Retrieval-augmented Generation (RAG), Generative AI, Distributed Systems, Multivariate Statistical Modeling, GPU Computing, Big Data, Web Scraping, Unsupervised Learning, Generative Pre-trained Transformer 3 (GPT-3), Revenue Optimization, Pricing Strategy, Handwriting Recognition, DeepSpeed, Stable Diffusion, NVIDIA TensorRT, Software Architecture, OpenAI GPT-3 API, Financial Modeling, Cognitive Behavioral Therapy (CBT), Data Structures, User Journeys, Customer Journeys, Amazon API Gateway, Generative Artificial Intelligence (GenAI), Point Cloud Data, Application Packaging, Internet of Things (IoT), Industrial Internet of Things (IIoT), Rankings, Computational Biology, Oncology & Cancer Treatment, Genomics, Molecular Biology, Biology, A/B Testing, Bittensor, 3D, Diffusion Models, ControlNet, Data Strategy, Data, User Interface (UI), Airtable, Web Applications, Natural Language Understanding (NLU), Point Clouds, LangChain, Multimodal GenAI, Integrated Development Environments (IDE)

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