Position: Machine Learning Engineer/Computer Vision Engineer
Category: Data Science
English level: upper
Years of experience: 3

- Hackaton Smart City ( April 2018, Klaipeda. Lithuania) ( 2nd prize )

 - Hackaton Industry 4.0 ( Klaipeda Technology park, 2018) ( 1st prize)
I am software engineer with strong math and physics background. I had scientific backfround working with physical and math modeling (COMSOL Multiphysics, Wolfram Mathematica, Matlab, Origin), now my main domains are data science (R, numpy, pandas, scikit-learn), machine learning (TF, Keras, PyTorch, fastai, deeplearning4j) and web (Python/Django/Flask/JS). I am familiar with computer vision and NLP AI-subdomains

I was responsible and delivered solutions in following tasks

 -as Researcher I was developed computer models of processes in quantum-cascade lasers using computer algebra system Wolfram Mathematica, Matlab, Origin etc

- as Data Scientist I delivered data analysis for car sharing domain (theory of graphs, spatial geometry, recommentadional systems, optimization tasks) using Python libraries and tools: scikit-learn, pandas, networkx, osmnx 

- as AI Research Scientist was involved for Mars surface anomalies detection project (I had worked with Siamese Networks group approach)

- I took part in dozens of Computer Vision tasks solutions, such as object recognition, tracking and segmentation (in real time). I am familiar with popular architectures, models, datasets, approaches, whats "under the hood" of CNNs and GANs. Also I have expirience with 3D in CV (3D scene reconstruction/recognition and segmentation).

- as Machine Learning Engineer in NLP domain (gensim, nltk, spacy, tfidf, word(doc)2vec, RNN’s, BERT, GPT-2), supporting of AI-based endpoints (docker, EC2, Flask)

- as Deep Learning Engineer in developmet of Deep Learning framework for Java deeplearning4j.org I was responsible for connecting "underhood" part written on C++ with Java, I provided integration testing, Keras and PyTorch integration etc

- as Scientific Application Developer at the moment I apply DS&ML to life sciences (bio/cheminformatics, protein structure predicting and visualization, DNA/RNA sequences analysis) working in wide stack: Python, R, Matlab/Octave, Dart, JS.
I expect flexible shedule, RnD, non-sovietic style managament
I do NOT preffer plenty of long non-productive meetings (better save time for engineering&coding)