Michael Okuboyejo
Backend Engineer at HelloFresh
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolMichael Okuboyejo is a backend engineer with 11 years of experience building high-availability, scalable web services and APIs, currently crafting resilient systems at HelloFresh in Berlin. Trained as an electrical engineer, he blends hardware-rooted analytical thinking with software craftsmanship across Go, Java, Python and JavaScript, and production-ready stacks including Kubernetes, Docker and Terraform. He has deep experience in payments, media management and messaging systems from early-stage work at Kudi, where he was the second engineering hire and built core microservices and automation tooling. Passionate about distributed systems, AI and robotics, he routinely designs for fault tolerance and operational simplicity using PostgreSQL, MongoDB, Kafka and Redis. Outside day-to-day engineering he has a track record of technical leadership from university IEEE roles to organizing large events, reflecting an ability to scale teams and technical practices as well as systems.
11 years of coding experience
3 years of employment as a software developer
BSc. Electronics and Electrical Engineering, Electronics and Electrical Engineering, BSc. Electronics and Electrical Engineering, Electronics and Electrical Engineering at Obafemi Awolowo University
Stackoverflow
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0reached
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Github Skills (53)
sms-messages8
image-resizer7
resize-images7
sms-client7
simple-linear-regression7
cgo7
png6
sms6
smpp6
api-platform6
image6
logistic-regression5
api5
jpeg5
webp5
Programming languages (7)
Github contributions (5)
michaelokuboyejo/inception-network-in-keras
Apr 2020 - Dec 2022
This simple project is a Keras implementation of a simple Inception Network.
Contributions:21 PRs, 21 pushes, 20 branches in 2 years 8 months
inception-networkdeep-learningtensorflowkerassimple-project
michaelokuboyejo/Lenet5DigitRecognizer
Apr 2020 - Dec 2022
This simple project is a Keras implementation (with a few architectural changes) of the famous LeCun et al., 1988 paper on Convolution Neural Networks.
Contributions:16 PRs, 16 pushes, 16 branches in 2 years 8 months
keras-modelsdeep-learningkeras-neural-networkslenet-5convolution
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