Sebastian Lettner
Founding Engineer at Zauber
Munich, Bavaria, Germany
Summary
🤩
Rockstar🎓
Top SchoolSebastian Lettner is a Munich-based founding engineer with 7 years of experience building cloud-native AI products, developer tooling, and full-stack demos. Trained as an electrical engineer at TUM, he blends research-grade ML and distributed systems experience (Kubernetes, Docker, TF) with hands-on product work from frontend to DevOps. He has shipped audio retrieval and AI features at Jina AI and BCG X, improved CI/CD and testing infrastructure for prominent open-source projects like jina-ai/serve, and helped scale example apps and encoders across repositories. Comfortable moving between prototyping and production, he’s also co-founded TUM.ai and led student-facing ML initiatives—evidence of a knack for translating research into usable products. Outside engineering he’s drawn to startups, fashion, music and sports, bringing a creative, multidisciplinary perspective to technical problems.
6 years of coding experience
8 years of employment as a software developer
Master of Science - MS Electrical and Computer Engineering, Master of Science - MS Electrical and Computer Engineering at Technical University of MunichManage&More Scholarship, Manage&More Scholarship at Manage and More by UnternehmerTUMAbitur, Abitur at Gymnasium Oberhaching
English, German
Github Skills (19)
kubernetes10
docker10
pytest10
python10
testing10
dockers10
semantic-search10
cicd10
deeplearning-ai10
deep-learning10
kubernetes-pods10
jina10
cloud-native9
nlp9
fastapi8
Programming languages (5)
Github contributions (5)
jina-ai/examples
Apr 2021 - Jul 2021
Jina examples and demos to help you get started
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:70 reviews, 33 commits, 21 PRs in 2 months
Contributions summary:Sebastian's commits primarily involve modifying example code within the Jina AI examples repository. They focused on updating executor signatures, defining encoders, adding S3 scripting functionality, and implementing timing examples to measure QPS. Code changes span multiple example applications, indicating work on various components of the example projects. The user also contributed to refactoring and updating existing code.
nlppythononboardingget-starteddeep-learning
jina-ai/serve
Feb 2021 - Sep 2021
☁️ Build multimodal AI applications with cloud-native stack
Role in this project:DevOps Engineer & Test Automation Engineer
DevOps Engineer & Test Automation EngineerContributions:10 reviews, 45 commits, 11 PRs in 7 months
Contributions summary:Sebastian primarily focused on improving the testing infrastructure and automation within the `jina-ai/serve` repository. They implemented and modified unit tests, integration tests, and mocked external calls, particularly related to Docker and Hub usage. Furthermore, they contributed to the Continuous Integration and Continuous Deployment (CI/CD) process, with specific focus on Kubernetes deployment. The user demonstrated expertise in testing methodologies, Docker, and Kubernetes, ensuring the reliability and maintainability of the project.
opentelemetryllm-inferencecreative-aigrpcproduction
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