Muhammad Fahad Baig

In his role as an ML Operations Engineer L4 at Motive since February 2024, Muhammad Fahad Baig has engineered and implemented high-performance, scalable inference workloads utilizing Kubernetes and NVIDIA Triton. This achievement resulted in an impressive 15x reduction in AI inference costs and a 10x improvement in processing speed. Furthermore, he enhanced service visibility by integrating powerful monitoring tools such as Grafana, Prometheus, and Datadog, enabling better tracking of system performance and reliability. Fahad also revamps Motive's Customer Visualization pipelines in C++, leveraging advanced technologies like OpenCV and FFmpeg to decrease video processing and encoding times by five times. Currently, he is focused on implementing innovative agentic workflows using large language models (LLMs), embedding models, and vector stores (Qdrant) to facilitate efficient video retrieval and event reporting.

As a Full-Stack Engineer (Contractor) at Toptal from February 2024 to September 2024, Fahad led the development of a Minimum Viable Product (MVP) marketplace application specifically for the Black community. He architected the backend infrastructure using FastAPI, Python, and Elasticsearch, integrating payment solutions using Stripe for seamless transactions and subscriptions. He played a crucial role in building large-scale jobs for comprehensive website crawling, employing rotating proxies and Selenium, which included extensive natural language processing (NLP) pipelines for tokenization and embeddings to efficiently feed data into Elasticsearch indexes.

During his tenure as a Senior Software Engineer at Entertainers FZ from November 2022 to February 2024, Fahad developed RESTful microservices using Flask, SQLAlchemy, and MariaDB, implementing Session and JWT Authentication for various product features. One of his significant contributions was engineering a dynamic multi-tenant database connection within APIs, which effectively reduced code redundancy and database overhead, enhancing performance by 30%. Additionally, he built data warehouses to consolidate data from diverse sources like Salesforce and various database systems into Snowflake and Elasticsearch indices. His leadership in migrating all microservices to Python 3.11 involved not only code upgrades but also mentorship for developers on best practices to ensure high-quality code.

As an Artificial Intelligence Engineer at CureMD from July 2020 to November 2022, Fahad engineered an automated resume parsing and scoring system employing advanced frameworks like TensorFlow, PyTorch, and Spacy. He pioneered the design of a multi-threaded RabbitMQ-based audio transcription and hold-detection system, achieving 85% accuracy in automatic speech recognition (ASR) and hold detection through advanced NLP methods. His work also included leading the development of an automated Fax OCR system for patient information and lab reports, which greatly reduced data entry errors and digitized crucial medical records. Moreover, he crafted a machine learning-based ID card information extraction engine using YOLO and PaddlePaddle to automate patient registration workflows, while mentoring teams and making strategic architectural decisions that fostered innovation and enhanced system efficiencies.

Muhammad Fahad Baig holds a Bachelor of Engineering in Electrical Engineering from NUST (National University of Sciences and Technology) in Islamabad, Pakistan, where he achieved a CGPA of 3.71 out of 4.00. In addition to his engineering degree, he completed a Minor in Business Management with a CGPA of 3.88 out of 4.00. This strong educational foundation has equipped him with both technical and management skills applicable in various professional contexts.