Marc Sonnenfeld is a solutions-focused software engineer with 11 years of experience building distributed, microservices-based systems and observability platforms across Java and Go. He has delivered SaaS CRM and integration platforms, designed event-driven architectures with Kafka and RabbitMQ, and implemented tracing and metrics tooling from scratch to unify observability in service mesh environments. Skilled in OOP, SOLID, Hexagonal architecture and CQRS, he pairs strong database and SQL expertise with pragmatic performance tuning and profiling work. An active contributor to the GoCV computer-vision library, he expanded core matrix and linear-algebra capabilities used in DNN and OpenCV integrations. Based in Barcelona, he blends hands-on engineering with a teacher’s instinct—regularly driving best practices, code quality, and cross-team adoption of observability.
12 years of coding experience
15 years of employment as a software developer
Software Engineering, Software Engineering at University of California, Berkeley
Functional Programming Principles in Scala, Infor, 94.7%, Functional Programming Principles in Scala, Infor, 94.7% at Ecole polytechnique fédérale de Lausanne
Bachelor Business Administration Information Technology, Bachelor Business Administration Information Technology at Universitat de Girona
Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.
Role in this project:
Back-end Developer
Contributions:5 reviews, 18 commits, 18 PRs in 2 years 8 months
Contributions summary:Marc primarily contributed to the `gocv` library by implementing new methods for the `Mat` struct, a core component for image and matrix manipulation. These methods include `MeanStdDev()`, `Sort()`, `Trace()`, `SortIdx()`, `Reduce()`, `Solve()`, `SolveCubic()`, `SolvePoly()`, `Repeat()`, `PolarToCart()`, `ScaleAdd()` and `SetIdentity()`, significantly expanding the library's functionality for image processing and computer vision tasks. The contributions focused on providing more comprehensive array operations, linear algebra solvers, and utility functions, aligning with the project's computer vision and OpenCV focus.
Contributions:77 commits, 44 pushes, 3 branches in 1 day
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