Gerard Castell
Product Engineer at Fence
Barcelona, Catalonia, Spain
Summary
👤
Senior🎓
Top SchoolGerard Castell is a product-focused software engineer with eight years of experience building end-to-end web and telecom-infused systems from problem framing to production. Based in Barcelona, he’s moved from backend and frontend roles into senior engineering and tech lead responsibilities at Cleverea and now shapes product engineering at Fence. His background in telecommunications and a master’s specialization in deep learning for multimedia gives him a practical edge for data-rich, real-time applications. Gerard combines hands-on full-stack development with leadership in shipping reliable customer-facing features, and he often bridges ML prototypes into production services. Colleagues describe him as comfortable toggling between low-level system details and high-level product tradeoffs, making him effective at turning complex requirements into usable, deployable software.
8 years of coding experience
7 years of employment as a software developer
Master's degree Advanced Telecommunication Technologies · Mention in Deep Learning For Multimedia Processing, Master's degree Advanced Telecommunication Technologies · Mention in Deep Learning For Multimedia Processing at UPC - ETSETB TelecomBCNBachillerato, Bachillerato at La Salle BonanovaUPC Universitat Politècnica de Catalunya
English, Spanish, Catalan, French
Github Skills (92)
testing10
extensible10
nx-workspace10
javascript10
yarn-workspaces10
monorepo10
cli10
angular10
typescript10
nrwl-nx10
build-system10
nodejs10
cypress10
nextjs10
workspaces10
Programming languages (4)
Github contributions (5)
gerardcastell/bilingualy
Mar 2020 - Apr 2020
Contributions:4 PRs, 134 pushes, 8 branches in 1 month
sergio-gimenez/anomaly-4G-detection
Dec 2020 - Dec 2024
Anomaly detection in 4G cellular networks. Explore ML solutions for the detection of abnormal behaviour of eNB (MLEARN - MATT 2020)
Contributions:2 PRs, 27 pushes, 9 branches in 4 years
autoencoderanomalyexploreanomaly-detectionmachine-learning
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