Adil is available for hire

Adil Mubeen

Verified Expert in Engineering

Machine Learning Engineer and Developer

San Francisco, CA, United States

Toptal member since December 18, 2024

Expertise

Computer Vision Machine Learning Deep Learning Artificial Intelligence NLP RAG Full-stack OpenAI Web Development LLM PyTorch TensorFlow Python DevOps Kubernetes

Bio

Adil is an experienced machine learning engineer who specializes in AI, deep learning, large language models (LLMs), Python, C/C++, retrieval-augmented generation (RAG), computer vision, and natural language processing (NLP). He's proficient in developing and deploying scalable ML systems using TensorFlow and PyTorch. Adil consistently delivers innovative, intelligent solutions tailored to clients' needs.

Portfolio

Digiverse

ChatGPT, Machine Learning, Natural Language Processing (NLP), Computer Vision...

Aridian Technologies

Artificial Intelligence (AI), Computer Vision...

Malta Themes

Artificial Intelligence (AI), Machine Learning, Deep Learning, Computer Vision...

Experience

Retrieval-augmented Generation (RAG) - 7 years
Machine Learning - 7 years
Python - 7 years
Generative Artificial Intelligence (GenAI) - 7 years
Artificial Intelligence (AI) - 7 years
Large Language Models (LLMs) - 5 years
ChatGPT - 3 years
LlamaIndex - 3 years

Availability

Part-time

Preferred Environment

PyTorch, Large Language Models (LLMs), Computer Vision, Machine Learning, Deep Learning, SQL, Python, Artificial Intelligence (AI), C, DeepStream SDK

The most amazing...

...AI customer support platform I've built leverages LLMs and NLP to automate responses, enhance accuracy, and improve user satisfaction.

Work Experience

Machine Learning Engineer

2022 - 2024

Digiverse

Led a team of six ML engineers and worked on the production-ready deployment of a construction CV system, including diffusion models for real-time rendering of safety compliance and unsafe behaviors that reduced accident rates by 12%.
Worked hands-on on diffusion models, especially model inference optimization for retail video analytics and Azure deployments, using behavior analysis to monitor customer engagement and optimize store layouts, which increased profit by 10%.
Developed and optimized LLM algorithms and infrastructure for an AI customer support platform, achieving an 80% reduction in response time and a 65% decrease in operational costs through parallel computing, CI/CD pipelines, and GPU acceleration.

Technologies: ChatGPT, Machine Learning, Natural Language Processing (NLP), Computer Vision, Python, Amazon Web Services (AWS), Data Pipelines, AWS Data Pipeline Service, ChatGPT Prompts, ChatGPT API, Large Language Models (LLMs), Multiagent Generative Systems (MAGs), Deep Learning, Deep Reinforcement Learning, Deepfake, Big Data, Databases, Data Science, Data Scraping, Data Scientist, Agile Data Science, Generative Artificial Intelligence (GenAI), You Only Look Once (YOLO), YOLOv5, Large Language Model Operations (LLMOps), Machine Learning Operations (MLOps), DevOps, C++, C, C#, iOS, Swift, TensorFlow, PyTorch, PyTorch3D, PyTorch Lightning, Python 3, Git, GitLab, CI/CD Pipelines, GitLab CI/CD, Retrieval-augmented Generation (RAG), Data Classification, AI Data Classification, Docker, Kubernetes, Kubernetes Operators, Azure, Azure SQL, SQL, MySQL, NoSQL, PostgreSQL, MongoDB, Google Cloud, BigQuery, Google BigQuery, Google Bigtable, Amazon Marketplace Web Service (MWS), Amazon SageMaker, Chatbots, Speech to Text, Text to Speech (TTS), Speech to Text AI, Image to Text, Text to Image, NumPy, Pandas, Transformers, Data Transfers, Data Cleaning, Data Cleansing, Data Annotation, Data Analysis, Data Analytics, Oracle Database, Models, Modeling, Tableau, Spark, SpaCy, Spark ML, Spark NLP, Spark SQL, Data Lakes, Data Labeling, Web Development, APIs, Back-end, Back-end Development, DeepStream SDK, Data Inference, Azure Machine Learning, Supervised Machine Learning, Amazon Machine Learning, Object Detection, Microsoft Excel, Business Analysis, Business Analytics, IT Business Analysis, AI Agents, AgentGPT, Django, Flask, Matplotlib, Scikit-learn, FastAPI, Infrastructure, Data Interfaces, Bayesian Inference & Modeling, Deepstream.io

Machine Learning Engineer

2019 - 2022

Aridian Technologies

Built ML models and data pipelines to ensure workers' safety on construction sites, leading to a 32% reduction in workplace injuries.
Worked on object detection, human pose estimation, and activity recognition.
Developed a resume management system that streamlined the candidate screening process, reducing analysis time by 90%. I also implemented NLP algorithms to improve resume parsing accuracy, increasing relevant candidate matches by 25%.
Created a conversational AI solution that helped over 3,000 children learn Spanish, English, and Chinese.

Technologies: Artificial Intelligence (AI), Computer Vision, Natural Language Processing (NLP), Machine Learning, Python, Python 3, Amazon Web Services (AWS), Deep Learning, Data Pipelines, ChatGPT, ChatGPT API, Chatbots, AI Chatbots, Large Language Models (LLMs), Large Language Model Operations (LLMOps), Multiagent Generative Systems (MAGs), PyTorch, TensorFlow, Generative Artificial Intelligence (GenAI), Multimodal GenAI, You Only Look Once (YOLO), Machine Learning Operations (MLOps), DevOps, TensorBoard, Retrieval-augmented Generation (RAG), Data, Big Data, Databases, Data Cleaning, Data Cleansing, Docker, Kubernetes, AWS Data Pipeline Service, ChatGPT Prompts, Deepfake, Deep Reinforcement Learning, Reinforcement Learning, Reinforcement Learning from Human Feedback (RLHF), BigQuery, Google BigQuery, Google Bigtable, BigTable, Data Science, Data Scraping, Data Scientist, Agile Data Science, Data Lakes, Data Labeling, C++, C, C#, iOS, Web, Web Development, iOS App Development, PyTorch3D, PyTorch Lightning, Git, GitLab, CI/CD Pipelines, GitLab CI/CD, Data Classification, Azure, Azure SQL, SQL, MySQL, NoSQL, PostgreSQL, MongoDB, Oracle, SQL Server 7, Image to Text, Text to Image, NumPy, Pandas, Matplotlib, Scikit-learn, Object Detection, Text Classification, Classification, Image Classification, Microsoft Excel, AgentGPT, AI Agents, Django, Flask, FastAPI, Infrastructure, Bayesian Inference & Modeling, Bayesian Statistics

Machine Learning Engineer

2018 - 2019

Malta Themes

Implemented a real-time fraud detection system with deep learning models in PyTorch, achieving 98% accuracy and preventing significant financial losses.
Created a computer vision-based quality control system utilizing You Only Look Once (YOLO) and TensorFlow, improving defect detection by 30% and reducing manual inspection costs.
Worked on memory, communication, and data loading optimization for a ticket-selling recommendation system that increased sales by 16%.

Technologies: Artificial Intelligence (AI), Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), You Only Look Once (YOLO), TensorFlow, Python, Python 3, ChatGPT, ChatGPT API, ChatGPT Prompts, Azure Machine Learning, Amazon Machine Learning, Amazon Web Services (AWS), Data Pipelines, Large Language Models (LLMs), Multiagent Generative Systems (MAGs), AgentGPT, AI Agents, PyTorch, PyTorch Lightning, PyTorch3D, Artificial Neural Networks (ANN), Generative Artificial Intelligence (GenAI), Multimodal GenAI, Multimodal Models, Big Data, Databases, Data Science, Data Analysis, Data Analytics, SQL, NoSQL, PostgreSQL, Oracle, MongoDB, Optical Character Recognition (OCR), Large Language Model Operations (LLMOps), DevOps, Retrieval-augmented Generation (RAG), LangChain, Data Classification, Docker, Kubernetes, Azure, Azure SQL, Google Cloud, Amazon SageMaker, ML Pipelines, AI Pipeline, GitLab, GitHub, Chatbots, OpenAI, OpenAI API, OpenAI Gym, NumPy, Pandas, C++, C, C#, Speech to Text, Text to Speech (TTS), Speech to Text AI, Speech Recognition, Speech Synthesis, Machine Translation, Reinforcement Learning, Deep Reinforcement Learning

Experience

Anti-theft Security Application

A Python, C, and NVIDIA DeepStream Anti-theft security project in which I implemented a real-time camera inference pipeline. The pipeline processed live video streams, integrating object detection and action recognition models, optimized with TensorRT for GPU acceleration to achieve low latency and high throughput. Python was used to manage the pipeline and integrate deep learning models, while performance-critical components, such as custom plugins for DeepStream, were written in C to optimize memory management and computational efficiency.

The system leveraged CUDA for parallel processing, enabling efficient handling of high-resolution video streams on edge devices like NVIDIA Jetson. Preprocessing tasks, including resizing, normalization, and batching, were designed to minimize data pipeline bottlenecks. Real-time alerts and metadata logging were incorporated to detect and flag suspicious activities, ensuring timely responses and detailed incident tracking for further analysis.

AI Customer Support Agent

One of my most notable achievements is developing an advanced AI customer support platform engineered entirely in Python. This system integrates Twilio to handle incoming calls, seamlessly converting speech to text using state-of-the-art speech recognition technologies. The transcribed text is then processed by ChatGPT and enhanced with RAG via LangChain, ensuring accurate and contextually relevant responses. The platform then delivers these responses to the user, employing Eleven Labs' text-to-speech capabilities, enabling natural and fluent voice interactions.

The entire solution is containerized using Docker and deployed on Google Cloud Platform (GCP) with Kubernetes, ensuring scalability, reliability, and efficient resource management. This end-to-end system automates customer support interactions and significantly enhances response accuracy and user satisfaction. By leveraging large language models LLMs and NLP, the platform provides a scalable and intelligent support system tailored to meet diverse client needs.

AI-powered Health Care Assistant

I spearheaded the creation of an AI-powered virtual healthcare assistant that leverages NLP and computer vision to interpret patient inquiries and analyze medical images. This platform processes voice and text inputs to provide accurate medical information and diagnostic support, enhancing patient care and streamlining healthcare services.

Deployed on Azure with Kubernetes orchestration, the system ensures high availability and scalability, while Docker containers facilitate seamless updates and maintenance. By integrating LLMs with specialized medical datasets, the assistant delivers reliable and context-aware responses, significantly improving patient engagement and operational efficiency for healthcare providers.

AI-powered Construction Workers Safety System

I developed and optimized ML models and data pipelines to enhance worker safety on construction sites, reducing workplace injuries by 32%. The system monitors site environments in real time by utilizing You Only Look Once (YOLO) for precise object recognition and advanced activity recognition algorithms. By integrating computer vision techniques with NLP, the platform can detect unsafe behaviors and potential hazards, ensuring immediate compliance with safety standards.

The solution, containerized with Docker for seamless deployment, leverages deep learning frameworks such as TensorFlow and PyTorch. Deployed on Google Cloud Platform (GCP) using Kubernetes, the infrastructure ensures scalability, reliability, and efficient resource management. The implementation includes CI/CD pipelines and GPU acceleration to optimize performance and facilitate rapid updates. This comprehensive approach automates safety compliance monitoring and provides actionable insights through robust data pipelines, significantly enhancing overall site safety standards.

Learn New language Chatbot for Students

https://meglanguages.com/

An innovative language learning platform for children, enabling them to learn English, Spanish, and Chinese interactively. Powered by ChatGPT’s LLM, the platform uses cutting-edge AI to provide personalized language instruction. Built with Python for back-end logic, Node.js for API handling, and Angular for a seamless web interface, it offers an engaging user experience. Features include real-time text-to-speech and speech-to-text capabilities, enhancing pronunciation and conversational practice. Deployed on Azure using Kubernetes and Docker, the platform ensures scalability and reliability for its 3,000+ active student base. Designed for young learners, it combines interactive lessons with adaptive AI, creating a fun and effective way to master new languages.

Education

2022 - 2024

Master's Degree in Artificial Intelligence

Monroe University - New York, USA

Certifications

JUNE 2019 - PRESENT

Deep Learning Specialization

Coursera

Skills

Libraries/APIs

PyTorch, TensorFlow, NumPy, Pandas, PyTorch Lightning, PyTorch3D, OpenAI API, Spark ML, Spark NLP, Amazon Marketplace Web Service (MWS), SpaCy, Matplotlib, Scikit-learn, Camera API

Tools

ChatGPT, You Only Look Once (YOLO), Tableau, Microsoft Excel, GitLab CI/CD, GitLab, Git, Spark SQL, OpenAI o1, Azure Machine Learning, Kubernetes Operators, BigQuery, Amazon SageMaker, TensorBoard, GitHub, OpenAI Gym

Languages

Python, C++, SQL, C, JavaScript, TypeScript, C#, Swift, Python 3, PHP, HTML, CSS

Frameworks

LlamaIndex, Spark, Hadoop, Django, Flask, Deepstream.io

Paradigms

DevOps, Agile

Platforms

Azure, Kubernetes, Amazon Web Services (AWS), Docker, Polyaxon, Oracle Database, Web, iOS, Oracle, WordPress, Amazon

Storage

Data Pipelines, Google Cloud, NoSQL, MongoDB, MySQL, Databases, AWS Data Pipeline Service, Azure SQL, PostgreSQL, Google Bigtable, Data Lakes, BigTable, SQL Server 7

Other

Large Language Models (LLMs), Computer Vision, Machine Learning, Deep Learning, Generative Artificial Intelligence (GenAI), Speech to Text, Artificial Intelligence (AI), Data Science, Natural Language Processing (NLP), Machine Learning Operations (MLOps), Retrieval-augmented Generation (RAG), Full-stack, OpenAI, Web Development, DeepStream SDK, ChatGPT Prompts, Multiagent Generative Systems (MAGs), ChatGPT API, Data Classification, CI/CD Pipelines, Chatbots, Transformers, Models, APIs, Large Language Model Operations (LLMOps), Back-end Development, Data Inference, Machine Learning Algorithms, Object Detection, Business Analysis, Business Analytics, Data Analysis, Data Analytics, Text to Speech (TTS), API Integration, Reinforcement Learning, Deep Reinforcement Learning, Data Scientist, Semantic Analysis, Architecture, Leadership, AI Agents, AgentGPT, Big Data, Deep Neural Networks (DNNs), Data Scraping, Data, Optical Character Recognition (OCR), Modeling, Virtual Machines, Speech to Text AI, Azure Text to Speech, IBM Watson Speech to Text, Agile Data Science, AI Research, Deepfake, YOLOv5, AI Data Classification, Google BigQuery, Image to Text, Text to Image, Data Transfers, Data Cleaning, Data Cleansing, Data Annotation, Data Labeling, Back-end, Supervised Machine Learning, Amazon Machine Learning, IT Business Analysis, AI Chatbots, FastAPI, Multimodal GenAI, Reinforcement Learning from Human Feedback (RLHF), iOS App Development, Text Classification, Classification, Image Classification, Full-stack Development, Speech Recognition, Machine Translation, Neural Machine Translation, Artificial Neural Networks (ANN), Multimodal Models, LangChain, ML Pipelines, AI Pipeline, Speech Synthesis, AWS Jam, ElevenLabs Solutions, Generative Pre-training Transformer, Azure IoT, Website Data Scraping, Feature Engineering, Infrastructure, Data Interfaces, Bayesian Inference & Modeling, Bayesian Statistics, Cloud, GPU Computing, NVIDIA A100 Tensor Core GPU, Serverless GPUs, Generative Pre-trained Transformers (GPT)

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