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Даніїл

Machine Learning Engineer

Considering positions: Machine Learning Engineer, Data engineer, AI engineer, Data Scientist, MLOps Engineer, NLP Engineer
Age: 20 years
City of residence: Dnipro
Ready to work: Remote
Considering positions:
Machine Learning Engineer, Data engineer, AI engineer, Data Scientist, MLOps Engineer, NLP Engineer
Age:
20 years
City of residence:
Dnipro
Ready to work:
Remote

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DANIIL OLIINYK
Machine Learning Engineer / NLP Engineer
B u i l t p r o d u c t i o n P I I r e m o v a l s y s t e m p r o c e s s i n g 3 l a n g u a g e s w i t h 9 7 % a c c u r a c y. E x p e r i e n c e
integrating LLM APIs, building REST services, and deploying to cloud infrastructure.

C O N TA C T S ( C h e c h R e p u b l i c / U k r a i n e )

Email: [open contact info](look above in the "contact info" section)
Te l e g r a m : h t t p s : / / t . m e / f i d u s _ v a l
L i n k e d l n : h t t p s : / / w w w. l i n k e d i n . c o m / i n / - d a n i i l - o l i i n y k - /
Git hub: https://github.com/Fidus1337

SKILLS
A I / L L M : O p e n A I A P I , Tra n s f o r m e r s , N L P, P ro m p t E n g i n e e r i n g
D ev to o l s / D ev O p s : D ev O p s : D o c ke r, A z u re ( C o n t a i n e r I n s t a n c e s , B l o b S to ra g e ) , G i t , L i n u x , G i t
Hub actions, CI/CD
We b ( Fro n t e n d ) : H t m l , C S S , J ava s c r i p t ( J S )
We b ( B a c ke n d ) : P y t h o n , Fa s t A P I , R E S T A P I , Po s t g re S Q L , M y S Q L , D j a n g o

P ro m p t e n g i n e e r i n g to o l s : C h a t G P T, C l a u d e , G ro k , C o p i l o t , G e m i n i , K i l o C o d e , C u r s o u r

WORK EXPERIENCE
PII Removal System — AI Engineer 6 months
(system for Anonymizing resumes)
6 month experience - https://pii.it-sprout.org.ua/

- Trained custom NER model (XLM-RoBERTa) achieving
97% accuracy on Ukrainian/Russian/English names —
outperforming Azure, AWS, Google on Slavic languages

- Built REST API with FastAPI processing 86 resumes
documents/minute

- Integrated OpenAI API for automated quality
verification
- Reduced costs 10-460x vs cloud NER solutions by
optimizing for CPU inference

- Deployed via Docker to Azure Container Instances with
Blob Storage for document processing

Languages
English (B2), Russian (Native), Ukraininan(Native), Czech (B1)

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