82 lines
4.2 KiB
Markdown
82 lines
4.2 KiB
Markdown
# Work-Experience
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- **Mar. 2023 to Sep. 2023:**
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- Developer for 2Lambda.co. Role migrated from just coding stuff to
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architecting and rewriting the whole software from the ground up using a
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small modular approach instead of the shaky one-off systems in place.
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Was later a "nanny for everything".
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- Did a lot of work to have self-documenting code (i.e. generate documentation
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from the actual values used in the program, not some comments that always
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get out of date)
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- Setting up a knowledge-base (Zettelkasten-approach) to track experiments and
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hyperlink them to the documentation generated above (and due to Zettelkasten
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you then get "this thing was used in Experiments a, b and c" automatically
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- Technologies used:
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- Clojure
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- Complete application was written in Clojure
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- Never touched that language before March - got up to speed in just 2
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days, poked the expert on the team detailed questions about the
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runtime-system after 1 month (like inlining-behavior, allocation-things,
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etc.)
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- Emanote
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- autogenerated & linked documentation of internal modules
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- integrated with manual written tutorials/notes
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- crosslinking documentation of experiments with documentation of modules
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- Web of knowledge
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- bidirectional discovery of things tried/done in the past to optimize
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finding of new strategies (meta-optimizing the decisions on what to
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optimize/try)
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- Infrastructure
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- Organized and co-administrated the 4 Root-Servers we had
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- Set up Kubernetes, Nexus, Docker, Nginx, letsencrypt-certs, dns-entries,
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etc..
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- **Oct. 2018 to Aug. 2021**:
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- ML-Specialist at [Jobware](https://jobware.de) (Paderborn; german Job-Advertising-Platform)
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- Extraction/Classification of sentences from JobAds (Requirements, Benefits,
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Tasks, ...)
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- Extraction of Information from JobAds (Location of company, Location of
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workplay, contact-details, application-procedure, etc.) including geocoding
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of those information (backed by OpenStreetMap)
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- Embedding of JobAds into a meaningful space (i.e. "get me similar ads. btw.
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i dislike ad a, b, c").
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- Analyse & predict search-queries of users on the webpage and offer likely
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but distinct queries (i.e. similar when typo or complete different words
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(synonyms, hyponyms, etc.))
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- Technologies used:
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- Haskell (currently GHC 8.6, soon GHC 8.8)
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- stack + stackage-lts
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- fixplate (recursion-schemes-implementation)
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- many usual technologies like lens, http-simple, mtl, ..
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- golden-testing via tasty
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- several inhouse-developments:
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- templating based on text-replacement via generics (fieldname in
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Template-Type == variable replaced in template)
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- activeMQ/Kibana-bridge for logging via hs-stomp
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- generic internal logging-framework
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- Python
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- tensorflow
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- pytorch
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- sklearn
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- nltk
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- **2013-2018**:
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- several jobs at my University including
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- Worked 6 Months in the Workgroup "Theoretical Computer Science" on migrating
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algorithms to **CUDA**
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- Tutor "Introduction to Machine Learning"
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- Was awarded **Tutoring-Award** of the Faculty of Technology for excellent
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tutoring
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- Lecture "[[FFPiH|Intermediate Functional Programming in Haskell]]"
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- Originally developed as student-project in cooperation with Jonas Betzendahl
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- First held in Summer 2015
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- Due to high demand held again in Summer 2016 and 2017
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- Was awarded **Lecturer-Award** "silver Chalk" in 2016
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- First time that this award was given to students
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- Many lecturers at our faculty never get any teaching-award until retirement
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- Development of Pandoc-Filters for effective **generation of lecture-slides**
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for Mario Botsch (Leader "Workgroup Computer Graphics") using Pandoc & reveal.js
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- Framework: [https://github.com/mbotsch/revealSlides](https://github.com/mbotsch/revealSlides)
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- Example: [https://github.com/mbotsch/eLearning](https://github.com/mbotsch/eLearning)
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- Pandoc-Filters: [https://github.com/mbotsch/pandoc-slide-filter](https://github.com/mbotsch/pandoc-slide-filter)
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