Vetted Algorithms Professionals

“Backend/platform engineer with significant ownership at GoDaddy, where they built a real-time personalization and decisioning system that drove about $7M in annualized revenue and serves roughly 4M requests per day. Also operates as a solo engineer for a global human-rights legal-tech nonprofit, building the full platform and graph-based matching engine for 700+ partner organizations. Brings a strong blend of production backend rigor, platform thinking, and practical AI orchestration.”

“Former founder/COO of Modjoul who spent 9.5 years building and scaling the company, including multiple pre-seed and seed raises and growth to 12M with Amazon. Brings a rare mix of operator grit, startup finance discipline, accelerator mentorship through CDL Wisconsin, and hands-on GTM/product launch experience with an 'all costs' founder mentality.”

“Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.”

Tom Dinwiddie

Screened

Executive IT Leader specializing in global SaaS, cloud transformation, and M&A integration

20y exp

“Technology executive/CTO-type leader with experience at ALLDATA defining and operationalizing an executive-prioritized roadmap, scaling distributed engineering teams (including expansion in Mexico and India), and modernizing products onto a containerized Google Cloud architecture. Highlights include 99.96% reliability, 38% maintenance cost reduction, and strong security/compliance posture (CyberArk, ISO27001, SOC2, SOX).”

“Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.”

“Postdoctoral/PhD researcher focused on Alzheimer's disease who has built scalable end-to-end AI systems across pathology imaging, transcriptomics, and longitudinal neuroimaging. Particularly strong in turning novel research ideas into robust Python pipelines on GPU/HPC infrastructure, with pathologist-facing impact and scientifically novel findings such as image-derived disease severity trajectories and subtype discovery.”