Ernesto Casas
Senior QA Engineer at GFT Group
Costa Rica
Summary
🤩
Rockstar🎓
Top SchoolErnesto Casas is a Senior QA Engineer with 13 years of experience delivering quality in banking, brokerage and marketing automation environments. He leads QA and SDET efforts, specializing in test automation and process improvement across backend, desktop, web and mobile using Selenium, Cypress, C#, Python and Azure DevOps. Holding a Master’s in Computer Science and numerous ISTQB and SAFe certifications, he combines formal testing rigor with hands-on CI/CD, release management and metrics-driven test strategies. Unusually for a QA lead, he has contributed backend performance work to the Broad Institute’s GATK (Genome Analysis Toolkit), optimizing PairHMM with AVX/OpenMP and experimental FPGA support, which highlights his systems and performance engineering depth. Based in Costa Rica, he focuses on embedding quality into the SDLC through automation frameworks, cross-functional coaching and measurable process improvements.
13 years of coding experience
18 years of employment as a software developer
Universidad de Costa RicaHigh School, High School at Sequoia High School, SF, CA, USA
English, Spanish
Github Skills (16)
avx10
bioinformatics10
javas10
exceldna10
genome10
genomics10
gatk10
ng10
java10
genomes10
openmp9
python8
fpga7
tensorflow26
tensorflow6
Programming languages (3)
Github contributions (5)
broadinstitute/gatk
Apr 2017 - Jun 2018
Official code repository for GATK versions 4 and up
Role in this project:
Backend Developer
Backend DeveloperContributions:13 commits, 12 PRs, 11 pushes in 1 year 1 month
Contributions summary:Ernesto significantly contributed to the GATK (Genome Analysis Toolkit) project by implementing and enhancing the PairHMM (Pair Hidden Markov Model) functionality. They focused on optimizing the PairHMM, introducing support for new interfaces, native arguments, and FPGA acceleration, leading to performance improvements. The user's work involved integrating and configuring native implementations like AVX and OpenMP for CPU acceleration, along with experimental FPGA support. They also modified the CNNScoreVariants module, improving input tensor preparation.
genomesciencednaspark-mlngs
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