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\title{Ridwan Salahuddeen - Resume}
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    \textbf{\Large Ridwan Salahuddeen} \\
    1040 Huff Road NW, Atlanta, Georgia 30318 \\

    \href{mailto:<PRESIDIO_ANONYMIZED_EMAIL_ADDRESS>}{\includegraphics[height=10pt]{resume_maker/assets/emailicon.png} <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS>} \quad
    \includegraphics[height=10pt]{resume_maker/assets/phone_icon.png} <PRESIDIO_ANONYMIZED_PHONE_NUMBER> \\
    \href{<PRESIDIO_ANONYMIZED_URL> ridwan-salahuddeen} \quad
    \href{https://www.github.com/ridwan-salau}{\includegraphics[height=10pt]{resume_maker/assets/github.png} ridwan-salau} \\
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\section*{Professional Summary}
Dedicated ML Engineer with \textbf{5+ years of experience} applying data science and engineering across financial institutions and start-ups. Expertise in \textit{ML model deployment, monitoring, and infrastructure management}. Strong background in \textbf{cloud technologies, container orchestration, and ML frameworks}. Passionate about core engineering and applied research, particularly in \textit{NLP and ML systems}.

\section*{Work Experience}

\textbf{Senior Data/ML Engineer} \hfill \textit{Jan 2023 - Present}\\
BeeKeeperAI (Via RigrAI) - California, US/Remote
\begin{itemize}[noitemsep,leftmargin=*]
    \item Adapted \textbf{BERT Language Model for private health data detection}, achieving \textit{97.3\% F1-score}
    \item Developed secure \textbf{Enclave infrastructure} for privacy-focused ML/healthcare data processing collaboration and implemented an extensive testing framework using \textit{Golang, Docker Compose, OpenAPI, Azure DevOps, and GitHub Action}
    \item Implemented \textbf{data attestation system} for zero-trust enclave interaction using Golang
    \item Tested \textit{PyTorch and Tensorflow frameworks} ML in Custom Escrow confidential computing systems, implementing more than 10 demo problems
\end{itemize}

\textbf{Senior Data/ML Engineer} \hfill \textit{Jan 2023 - Present}\\
RigrAI - Remote
\begin{itemize}[noitemsep,leftmargin=*]
    \item Co-led development of an \textbf{AI-enhanced security investigation tool} for Child Sexual Abuse Material investigation
    \item Implemented and integrated \textit{face clustering}, \textit{age estimation}, and \textit{optical character recognition} models to detect sensitive materials in streaming video materials
    \item Improved ML model serving using \textbf{Nvidia triton server} and \textit{model compilation}
    \item Developed well-structured and highly-decoupled \textbf{FastAPI web APIs} integrated with 8 separate ML modules, \textit{Elasticsearch, MinIO storage, Kafka, and Schema Registry} using Docker Compose for integration
\end{itemize}

\textbf{Research Assistant} \hfill \textit{Aug 2022 - May 2024}\\
Center for Integrative Artificial Intelligence - Remote
\begin{itemize}[noitemsep,leftmargin=*]
    \item Submitted the paper \textit{"Memoization-Aware Bayesian Optimization for AI Pipelines with Unknown Costs"} for publication
    \item Implemented \textbf{Transformer-XL with Fully-Sharded Data Parallel}, achieving \textit{100\% improvement in throughput}
    \item Applied \textbf{instruction fine-tuning with Llama and GPT-2} for text summarization
    \item Developed \textit{contrastive and cross-modal fusion models} for hate meme detection
    \item Adapted GPT-2 for cognitive bias detection in articles
\end{itemize}

\textbf{Senior Data/ML Engineer} \hfill \textit{Jan 2022 - Nov 2022}\\
Tribes.ai - Queensland, Australia
\begin{itemize}[noitemsep,leftmargin=*]
    \item Developed an integration pipeline for automated timesheets, revenue attribution, and data storytelling
    \item Developed a framework for dynamically generating and deploying client-specific \textbf{Airflow transformation pipelines} at sign-up
    \item Wrote and maintained highly optimized batch extraction and transformation pipelines with \textit{Python, Pandas, SQL, and Neo4j Cipher}
    \item Developed and tested \textbf{REST and GraphQL APIs} with Flask, BigQuery, and MySQL for the product's backend service
    \item Developed and deployed an optimized events logging pipeline for browser data, capturing thousands of events per second
\end{itemize}

\textbf{Data Scientist} \hfill \textit{Sep 2017 - Aug 2021}\\
Access Bank Plc - Lagos, Nigeria
\begin{itemize}[noitemsep,leftmargin=*]
    \item Led development of \textbf{enterprise sentiment management system}, including the web-scrapers, ML models for batch inference, and scheduled retraining feedback loop, saving over \$60,000
    \item Deployed Central Bank reporting solution using \textit{SQL}, \textit{Python}, \textit{Django} and \textit{Docker}
    \item Implemented \textbf{DBSCAN-based anomaly detection} to flag suspicious Banking transactions 
    \item Implemented \textbf{DBSCAN-based anomaly detection} for time-series data to flag Core Banking system downtimes within 40 seconds. 

\end{itemize}

\section*{Education}
\begin{itemize}[noitemsep,leftmargin=*]
    \item \textbf{MSc Machine Learning}, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi - May 2024
    \item \textbf{BSc Electronics and Electrical Engineering}, Ladoke Akintola University of Technology - Feb 2015
\end{itemize}

\section*{Certifications}
\begin{itemize}[noitemsep,leftmargin=*]
    \item \textbf{Microsoft Azure Certified:} Data Scientist, Data Engineer and AI Engineer
    \item Deep Learning Nanodegree, Udacity
    \item Data Engineering Nanodegree, Udacity
    \item End-to-End ML with Tensorflow on GCP and Production Machine Learning Systems, Coursera
\end{itemize}

\section*{Technical Skills}
\begin{itemize}[noitemsep,leftmargin=*]
    \item \textbf{Cloud Platforms:} AWS, Azure, GCP
    \item \textbf{ML/AI:} PyTorch, TensorFlow, Sagemaker
    \item \textbf{Big Data:} Spark, Kafka, Google BigQuery
    \item \textbf{Containerization:} Docker, Docker Compose, ECS
    \item \textbf{Orchestration:} Airflow, Kubeflow
    \item \textbf{Languages:} Python, R, SQL, Bash, Golang
    \item \textbf{Frameworks:} FastAPI, Flask, Pandas, NumPy, PySpark
    \item \textbf{Databases:} MySQL, Neo4j, Elasticsearch
\end{itemize}

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