Responsible for the people, processes, technology, and culture of OkCupid's backend engineering team. Focused on improving hiring process, incident response, and product quality.worked closely with the product team while splitting my time between engineering management and technical product management.Managed stakeholders, planned work, presented quarterly plans and progress to C-level executives.

I naturally fall into the Solver and Tech Lead archetypes as described by StaffEng.comhttps://staffeng.com/guides/staff-archetypes

SME of OkCupid's proprietary recommendations system.Modified and analyzed changes to the recommendations system.Designed and built complex infrastructure to handle high volume voting data.Led the tech team responsible for designing and implementing OkCupid's SMS authentication system used as both a primary and second factor authentication system.Led the tech team responsible for designing and implementing OkCupid's localization system across all platforms.

• Collaborated on an IRAD (Enterprise Sensors Laboratory – ESL) and operational program (Ballistic Missile Defense System Overhead Persistent Infrared Architecture - BOA) that utilizes overhead persistent infrared sensors, radars, and other intelligence assets to detect, track, and type ballistic missiles in real-time to provide cues to defense assets • Championed the use of machine learning and data conditioning in missile defense software by utilizing SVMs and neural nets for missile typing, false track detection, and other tracking purposes • Directed a group of three engineers tasked with completely redesigning and rewriting a complex real-time operational algorithm consisting tens of thousands of lines of C++ • Developed an in-depth knowledge large complex code base (C/C++/Fortran) and became the go-to engineer to solve mission critical problems quickly and correctly • Authored two and co-authored one internal conference presentations ◦ Bridging the Gap between Systems Engineering and Machine Learning – Demonstrated how machine learning can be leveraged in conjunction with traditional systems engineering methods to improve reliability and accuracy of classification algorithms ◦ Exploitation of State Covariance Estimates for Locating Active and Passive Sensor Assets – Demonstrated the importance of covariance convolution in order to prevent adversaries from determining sensor asset locations using state covariance estimates in low observability situations ◦ False Track Detection using Machine Learning – Provided insight to early successful efforts by myself and coworkers to determine false missile tracks using various machine learning techniques • Mentored computer science senior project groups from the University of Colorado at Boulder and University of Colorado at Colorado Springs tasked with developing a Convolutional Neural Net for automobile classification using PyTorch

• Collaborated on ESL and BOA • Designed and implemented automated requirements verification and analysis tools for moderately large data sets (10GB – 1TB) using Python, MatLab, and some Java and VBA • Developed real-time simulation tools for performance prediction using C/C++

- Build and modify software packages for deployment to computer labs- Manage student computer labs- Write and deploy custom software for the University of Colorado- Train new student employees