Vivek Verma
Verified Expert in Engineering
Machine Learning Developer
Gurugram, Haryana, India
Toptal member since January 8, 2021
Vivek has more than four years of experience developing end-to-end solutions based on machine learning (ML) and deep learning. He's worked on projects from different sectors including Fortune 500 pharmaceutical companies like Merck and Pfizer. Vivek excels at providing end-to-end solutions using ML not just coding an algorithm. Apart from being an expert in natural language processing, Vivek also has robust development skills with React and Django.
Portfolio
Experience
- Python - 8 years
- Django - 7 years
- Amazon Web Services (AWS) - 6 years
- Generative Pre-trained Transformers (GPT) - 4 years
- Natural Language Processing (NLP) - 4 years
- TensorFlow - 4 years
- Machine Learning - 4 years
- Docker - 2 years
Availability
Preferred Environment
Keras, TensorFlow, Python, Object-relational Mapping (ORM), Text to Image, Engineering, Artificial Intelligence (AI), Natural Language Understanding (NLU)
The most amazing...
...thing I've built was a propensity model using features tracked on the product website as well as conversation data from calls—it led to a 30% increase in sales.
Work Experience
Machine Learning Engineer
Leena AI
- Developed a complete ML back end to classify user queries from bot to more than 500 intents. This reduced prediction time per query by more than 5x and training time by 10x.
- Ideated and developed a front and back end to facilitate internal bot data creation and management, used by more than 15 analysts. Reduced bot development time by 2x.
- Developed a PDF Parser utility to prepare FAQs and parse tables out of scanned PDF documents, reducing the time required by a factor of 5x.
Machine Learning Engineer
PolicyBazaar
- Achieved a 25% increase in lead conversion and a 30% increase in revenue by using an AI-lead ranking algorithm.
- Built a lead rejection model using call transcriptions data, leading to an estimated cost savings of 10%.
- Constructed an intent identification system for WhatsApp, resolving 50% queries without manual effort.
Data Scientist
Innoplexus
- Developed an NLP-based model to identify adverse reactions associated with a particular drug with an accuracy of over 80%.
- Built a state-of-the-art biomedical entity extractor to identify new biomedical entities from a corpus of biomedical abstracts, gaining more than 10% accuracy over the existing process.
- Developed an ML-based pipeline to identify publications associated with a clinical trial document which improved coverage by 4x.
Experience
Intent Classifier for Chatbots
Education
Bachelor's Degree in Mechanical Engineering
Indian Institute of Technology Delhi - New Delhi, India
Certifications
Deep Learning Specialization
Coursera
Skills
Libraries/APIs
TensorFlow, PyTorch, React, Google APIs, REST APIs, Keras, Scikit-learn
Tools
Named-entity Recognition (NER), AWS Deployment, Rasa.ai
Languages
Python, JavaScript, SQL, TypeScript
Platforms
Firebase, Docker, Amazon Web Services (AWS)
Storage
Databases, Cloud Firestore, PostgreSQL, Elasticsearch
Frameworks
Django, Flask
Paradigms
Object-relational Mapping (ORM)
Other
Machine Learning, Natural Language Processing (NLP), Computer Vision, Artificial Intelligence (AI), APIs, Image Classification, Generative Pre-trained Transformers (GPT), OpenAI GPT-3 API, Engineering, Natural Language Understanding (NLU), Fine-tuning, Graphics Processing Unit (GPU), PDF Scraping, Scraping, Language Models, Web Scraping, Website Data Scraping, Back-end, Large Language Models (LLMs), Data Science, Computer Vision Algorithms, Chatbots, Webhooks, Text to Image, Async Batch Processes, Deep Learning, Data Structures
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