Ahmed Wahid
EXPERTISE
BIO
I'm a seasoned software engineer with 5+ years of experience developing data-driven applications and machine learning systems. My background spans both research and production environments, where I've designed and implemented solutions for natural language processing, recommendation systems, and data analysis pipelines. I excel at translating complex requirements into elegant solutions, optimizing performance, and ensuring production reliability. My experience includes working with Python, TensorFlow, PyTorch, and deploying models at scale using cloud services. I'm particularly skilled at fine-tuning models for specific domains and building robust data processing pipelines.
WORK EXPERIENCE
Senior ML Engineer
Meta
January 2023 - Present
• Developed and deployed NLP systems using transformer-based models that increased customer service automation by 65% and improved sentiment analysis accuracy to 92%. • Fine-tuned large language models (LLMs) for domain-specific applications, reducing training time by 40% while maintaining 95% performance compared to full retraining. • Implemented retrieval-augmented generation (RAG) systems that enhanced LLM accuracy by 30% on company-specific knowledge tasks. • Built computer vision models for image classification and object detection using PyTorch that achieved 96% accuracy in production environments. • Designed ML pipelines using Kubeflow that automated model training, evaluation, and deployment processes, reducing time-to-production by 70%. • Created comprehensive model monitoring systems that detected drift and triggered retraining processes, maintaining model performance in changing environments. • Optimized inference performance through model quantization and distillation, reducing latency by 65% and resource usage by 80%. • Collaborated with cross-functional teams to identify AI opportunities and translate business re- quirements into technical solutions.
Machine Learning Engineer
Microsoft
March 2021 - December 2022
• Implemented recommendation systems using collaborative filtering and deep learning techniques that increased user engagement by 45% and content discovery by 35%. • Developed data preprocessing and feature engineering pipelines that improved model accuracy by 25% while reducing training time. • Built and deployed machine learning models using TensorFlow and scikit-learn for classification, regression, and clustering problems across various domains. • Created ETL processes for handling large-scale datasets (10TB+) with efficient data cleaning, transformation, and loading strategies. • Containerized ML services using Docker and deployed them on Kubernetes clusters, ensuring scal- ability and reliability in production. • Implemented A/B testing frameworks for evaluating model performance in real-world environments and making data-driven improvement decisions. • Collaborated with data scientists to transform research prototypes into production-ready systems with appropriate engineering practices. • Developed AI ethics guidelines and implemented bias detection and mitigation strategies for sen- sitive ML applications.
EDUCATION
MSc
Georgia Institute of Technology, March 2021
Computer Science
Verified Machine Learning Engineer
3-5 years of experience
Preferred commitment: Full Time
Languages
Skills
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