Ongun Tuna is a Machine Learning and Speech Processing Engineer with 13 years of software engineering experience and over five years focused on applied ML, NLP and speech systems, currently based in the Berlin area. He builds end-to-end ML pipelines and deployable models for real-time and embedded audio applications, having improved denoiser inference performance by 30% and optimized LLM-driven healthcare assistants using LangChain and VectorDBs. His background blends academic research—four conference abstracts and reinforcement-learning safety work at Fraunhofer—with hands-on cloud and DevOps contributions to notable open-source projects like kubernetes/kompose and kubeapps. Comfortable across back-end, DevOps and full-stack roles, he has a track record of shipping production-ready solutions that bridge signal processing, ML research and scalable deployment. Notably, he ported and hardening CLI tooling for kompose and added Kubernetes event handling features integrated with Slack for kubewatch, reflecting his strength in developer tooling for cloud-native ecosystems. He seeks opportunities to apply applied research and MLOps best practices to real-world products that demand both rigor and pragmatic engineering.
13 years of coding experience
4 years of employment as a software developer
Abitur, Abitur at Istanbul Erkek Lisesi
Nanodegree, Cloud DevOps Engineer, Nanodegree, Cloud DevOps Engineer at Udacity
Master of Science, Electrical and Electronics Engineering, Master of Science, Electrical and Electronics Engineering at Technische Universität München
Contributions:2 releases, 30 commits, 15 PRs in 11 months
Contributions summary:Ongun primarily contributed to the project by adding and modifying Go code related to Kubernetes event handling and Slack integration. Their work included enhancing Slack messages to include object names, fixing identified bugs related to event processing, and integrating with external dependencies. They also introduced Cobra commands for project configuration, laying the groundwork for more sophisticated command-line interactions and configurations.
Contributions:5 releases, 68 PRs, 103 pushes in 3 years 3 months
Contributions summary:Ongun contributed significantly to the project by adding the initial CLI implementation, potentially porting it from a kompose-lite version. They integrated a Makefile for build automation, and also updated dependencies, specifically downgrading the urfave/cli library. Further contributions included fixing an output issue by saving Kubernetes objects into a single file and supporting docker bundles format. The user has also refactored and cleaned convert function, as well as added some test, which involved in converting docker compose to k8s objects.
containersgolangdockercomposedocker-compose
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