
Catewalker
Eng.
California City40 USD/hourMember since May 4, 2026
PythonC#JavaScriptTypeScriptSQLAssembly (x86/ARM)PandasNumPyScikit-learnXGBoostTensorFlowPyTorchGhidraIDAx64dbgCryptographyBinary ExploitationMongoDBPostgreSQLRedisDockerKubernetesLinuxGitCI/CD.NET 8ASP.NETFastAPIReactVue.jsSoftware EngineeringCybersecurity & Reverse EngineeringMachine Learning EngineeringData ScienceC# / C++ Systems ProgrammingDistributed SystemsAI SecurityHigh-performance ComputingOpenCVPython DashAWS EC2Node.jsExpressSocket.ioChart.jsradare2JWTSHA256
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About
Harvard University CS & Mathematics student (GPA 3.96/4.0) with deep expertise in software architecture, cybersecurity, and applied machine learning. Proven track record in high-performance C# systems, reverse engineering, and fraud analytics. Combines mathematical rigor with pragmatic engineering to deliver secure, scalable solutions. Kaggle top 3% performer and active security researcher.
Experience
Senior SAS Developer at nvGate Service Management (2024-01 – Present)
- Architect and maintain high-throughput backend services using C# / .NET 8, handling 50k+ API requests per minute with sub-100ms latency.
- Implemented security-focused middleware (JWT, SHA256 request signing) and anomaly detection pipelines for real-time threat analysis.
- Designed data processing pipelines with C# and MongoDB, reducing ETL execution time by 37%.
- Collaborated with security teams to reverse-engineer malicious payloads and strengthen API defense mechanisms.
Machine Learning Engineer Intern at Greenway Farms (2024-06 – 2024-08)
- Developed end-to-end computer vision pipeline using OpenCV and PyTorch to detect crop diseases from drone imagery, achieving 94% accuracy.
- Engineered time-series models for yield prediction based on weather and soil moisture data, increasing forecast precision by 22%.
- Built interactive dashboards using Python Dash and deployed models via Docker containers on AWS EC2.
Data Science Analyst at Miller's Family Farm (2023-01 – 2023-08)
- Analyzed 10+ years of soil composition and microclimate data using Python to optimize water usage.
- Delivered predictive irrigation scheduling model that reduced water consumption by 18% while maintaining crop yield.
- Presented actionable insights to farm management and translated ML outputs into operational changes.
Education
Bachelor of Arts in Mathematics & Computer Science – Harvard University (2022-01 – 2026-01)
Skills
Eng.