lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Machine Learning Engineer
Category: Python
Experience: 0.5 years | English: upper

Samsung Project Intern(Voice Authentication) 
January 2019-February 2019

Data Obrii, Data Science Intern (NLP tasks, Data Analysis) 
September 2019 - December 2019
Skills:
Python with machine learning stack:
    - Sorting,graphs,trees and algorithms
    - Deep learning (Neural Networks)
    - matplotlib,numpy,tensorflow,sklearn,pandas,SQLite3
    - Flask

Good knowledge of Java and R

Courses:
   - Deep Learning Specialization on Coursera (by deeplearning.ai)
Work Experience :
 1)Samsung Project Intern(Voice Authentication) 
January 2019-February 2019

2)Data Obrii, Data Science Intern (NLP tasks, Data Analysis) 
September 2019 - December 2019
    
My own projects : 
1)Simple file sharing - Web service using Flask and Python : 
Simple file-sharing services with user registration and authorization support. Uses: Python, Flask, SQLite3

2)Google Trends analyzing with R
I want to be a part of the ambitious team and implement my skills in real projects
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent


TB Detection from Chest X-ray: | OpenCV, Django, TensorFlow, SQL
• Used a pre-trained U-Net model with 97% dice coefficient and MobileNetV2 with 98% for lung area segmentation
and Lung disease classification.

Customer Clustering: | Pandas, Sci-kit-learn, Numpy, Seaborn, Matplotlib, Git
• Used data analysis and clustering to identify consumer experience, engagement, and satisfaction and found that
71% of the customers were satisfied with the service.

Creative Optimization: | TensorFlow, OpenCV, Sci-kit-Learn, DVC, MLFLOW
• Computer vision algorithms to extract features from creative assets and predict the related KPI performances.

Entity Extraction and News Artifact Classification: | Cohere, Python, Flask, Streamlit, Docker, MLFLOW, DVC
• Applied Large Language Model for extracting entities from job descriptions and classifying news given only a few
examples of human scores
Position: Machine Learning Engineer
Category: Data Science
Experience: 0.5 years | English: fluent

Winner of hackathon HackNU 2023 (2nd place, 400+ teams)
Winner of RBK Bank Hackathon 2022 (2nd place)
Winner of SDU Proficiency Test Olympiad
International Conference on Electronics Computer and Computation (ICECCO) 2023 Speaker
ICECCO 2021 Speaker
Author of Telegram channel 'IT Community of SDU' (2600+ subscribers, 2000+ views per post, collaborations with JetBrains, Beeline, Kolesa, and others.)
• Trained classification and segmentation model for MRI images and markups using PyTorch Lightning.
Performed hyperparameter tuning with Optuna. The dice score was 87%. Posted article on Medium.
• Implemented a service for processing MRI pictures and sending coordinates of segmented areas with OpenCV.
The service assisted the doctors to segment and detect the deceased areas of the brain.
• Trained classification and segmentation model of hemorrhagic stroke blood type for CT images using 2.5D
technique. It helped to decrease the weight of the model on the server and still classify and segment blood as
well as with 3D images.
• Made a live dashboard with Streamlit. Used Apache Airflow for DAGs management. The dashboard helped
to track the statistics of diagnoses by each week. Used pandas, matplotlib, seaborn, pylab. for EDA.
I want to find a position as Junior Machine Learning Engineer, where I could learn from my colleagues (mentors).
Position: Machine Learning Engineer
Category: Python
Experience: 2 years | English: upper


Trained NN for object classification using Siamese, TripletLoss approach,
optimized ones with onnx, tflite
Trained Siamese Tracking using SiamFC, SiamRPN
Implemented pipelines for videos parallel processing using python3
multiprocessing, threading.
Elaborated logic for events recording and reporting on AWS
Built pipeline for videos parallel processing using DeepStream.
Customized some modules, e.g events recording using pyds.
Evaluated detected events, collected metrics, improved models
Position: Machine Learning Engineer
Category: Data Science
Experience: 0.5 years | English: upper

As a trainee Machine Learning Engineer, I developed a Visual Localization project using 2D-3D transformations, OpenCV, Open3d, and CNN VGG-16. It's also well done and works fast in real-time.
I worked on an educational project during the CV/AI camp. It was a teamwork educational computer vision project for table tennis ball detection and tracking during tennis tournaments. YOLO v5 was used for transfer learning, OpenCV library, and computer vision techniques for tennis ball detection and tracking. My team developed the best project among all in the educational camp. I've reached an accuracy of 88% which is very good for the quality of input data.
Trainee Machine Learning Engineer:
Development of Visual Localization project using 2D-3D transformations, OpenCV, Open3d, CNN VGG-16. 
AI/CV Abto Software camp student:
Development of Table tennis ball detection project using computer vision techniques, OpenCV library, YOLO v5 model for ball detection.
Position: Machine Learning Engineer
Category: Python
Experience: 1 years | English: fluent

Finished courses online: 
edX | online learning platform 
- "ML0101EN: Machine Learning with Python" - 29/06/2022
- "Deep Learning Fundamentals with Keras" (IBM) - 06/2022
Coursera | online learning platform
- "Python Data Structures" - 06/09/2020 
- "Open Source Software Development Methods" - 23/11/2020
- "AI For Everyone" - 06/04/2020 
- "Introduction to Psychology" - 22/11/2020
Worked on a computer vision project on emotion recognition task using ML models to detect facial action units and facial expressions.
Worked on a interpretable human activity project, using different machine learning models for classification and Shapley values for interpretability.
Have experience in various projects in Python, using numpy, matplotlib, opencv, pillow, tensorflow, pytorch and scikit-learn.
Worked on an indie-game, written in GDScript, on Godot engine.
I am passionate Python developing. Ideally, machine learning projects, especially computer vision, but other areas, like natural language processing, are interesting for me as well.
Position: Machine Learning Engineer
Category: Data Science
Experience: 2.5 years | English: upper

• Invited to MIT Grand Hack for presenting AI healthcare project (2018) • Presented research on cigarette detector and collector rover robot at IEEE Conference. (2018) • 3rd place at Microsoft Imagine Cup regional finals for extracting cardio waves from old ECG machines and predicting cardio vascular diseases. (2018) • Got into the top 5 teams worldwide that advance to finals at Microsoft AI Guardian, for translating gesture language to text/audio and vice versa. (2019 Trainings • Nano-degree courses in self-driving cars and computer vision by Udacity President Sebastian Thrun (2018) • Computer vision course offered by Georgia Tech. (2018) • Deep Learning course by Geoffrey Hinton (2018)
Worked on AI models for secret military projects (2017 - Current)  
Implemented entrance check system based on face recognition (2018) 
Created end to end real time Text to Speech system on Georgian language (2019)
looking for the company that will help me to improve my skills as MA learning Engineer
Position: Machine Learning Engineer
Category: Data Science
Experience: 6 years | English: fluent

I once trained a bespoke computer vision model for reproductive cell assessments on less than 800 images which beat Google's Vision AutoML and a group of medical imaging PhDs.

More recently, I solved a document tagging problem using a BERT-based model for NER and covered four business use cases in one go. Also used synthetic data generation and the model mentioned above to grow a multilingual dataset.
Worked on NLP, CV, and time series projects. Led and mentored a team of 3 junior engineers. Among other things was also an MLOps, incrementally building and managing our ML infrastructure.
Position: Machine Learning Engineer
Category: Data Science
Experience: 1.5 years | English: intermediate


work experience
1 year: The private teacher of math
3 months till the war has started: Computer Vision Engineer (Junior position) in «Smartys»
8 months: Machine Learning Engineer (Computer Vision direction) in Sumix corp. 
1.5 year : Solution designer in OneReach.ai )
Position: Machine Learning Engineer
Category: Python
Experience: 4 years | English: upper

ML courses
Working with 3D pointcloud
Estimating 3D object parameters
Implementing PDF OCR pipeline, shape detection
Cables detection on pointcloud
Object parts detection
Segmenting pointcloud

3D bounding box estimation for ADAS system
Key Responsibilities:1. Technical leading team work, mentoring newcomers and trainees.
2. Preparing requirement specification based on customer information.
3. Coordinating and reporting project status with the customer.
4. Design and implementation pipeline for 3D box estimation
5. Migrating pipeline to TensorRT core
Technologies:Python, TensorRT, Nvidia Drive AGX, Pytorch, Keras, OpenCV, Deep Learning, Machine Learning


AI algorithms for Media and Content Management, Sport analytics

Key Responsibilities:1. Split Video into Scenes
2. Thumbnail & Caption from Scene
3. Compile Highlights from Video
3. Automated annotation of video and describing the events exposed
4. Search video by keywords describing a content
5. Extract the scene/event by a context description
6. Face recognition on video consequence
7. Predicting soccer events by video consequence
8. Creating and supporting soccer media system
9. R&D of detecting tiny objects
10. Creating Image Processing laboratory work course and teaching at university
Technologies:Deep Learning, Python, Machine Learning, Computer Vision, Image Processing

Audio ML processing
Key Responsibilities:
1. Tuning existing models
2. Creating new deep learning models for noise detection
I would like to work with Computer Vision, Deep Learning, Machine Learning
Position: Machine Learning Engineer and Researcher
Category: Python
Experience: 1 years | English: fluent

A few of my programming achievements are:
 Empowering a great product with AI capabilities that are used by Fortune 500 companies
 Integrating deep learning models with a complex product rife with hundreds of features 
 Programming with design patterns to ensure easy code readability and reusability
 Solving problems directly related to governments and law enforcement agencies
I have worked both as a Data Scientist and a Machine Learning Engineer. While working as a Data Scientist, I worked on a project of energy monitoring to identify flaws in a mixture being prepared by using machine learning. Here, I worked with time series data and include algorithms like Random Forest, LSTM, and Neural Networks in my analysis. My second experience is as a Machine Learning Engineer where I mainly worked with image data. Here, I developed solutions directly for law enforcement agencies and governments. These include a system to detect vehicles, along with their type, and color, and read their license number. I mainly used Pytorch for all the tasks, however, I am flexible enough to also handle tensor flow.
I want to work well under the ethical and legal boundaries.
Position: Machine Learning Engineer and Technical Team Lead
Category: Data Science
Experience: 4 years | English: intermediate


3 years experience working in Data Science and Machine Learning
2 years experience as Technical team lead
1 year experience as Product Owner of Analytical Platform
Working mostly on machine learning models deployment with Docker containers.
Core working language is Python
Other languages: R, Bash/Shell
Other Tools: Docker, Fast API, Bjorne, Falcon, Flask, Tensorflow, CUDA, WRK
Managing team of 14 people
Working mostly with big data modeling in financial industry for real time predictive analytics
Position: Machine Learning Engineer / Big Data Engineer
Category: Data Science
Experience: 3 years | English: upper

Implementing ML part of a photo editing app (from research to deployment) on one's own.
Bachelors diploma with honours.
Was invited to be a Mentor&Judge at hackathon.
Development of a system for analysis characteristics of cortical folding patterns on graphs (DL). Detecting anomalies financial data time series. Building a recommender system. Text tagging and speech-to-text research. ML part of a photo editing app. Music generation, Text classification. Creating an automated trading agent (Java).
Expect the company mission to be inspiring, including interesting and complex tasks. I am interested in studying new technologies, meeting new people and public speaking.
Position: Machine Learning Engineer (Computer Vision)
Category: Data Science
Experience: 1 years | English: upper

Prediction of number of total coronavirus cases in Ukraine, South Corea, USA, Kanada etc.

Repository with many educational code snippets in the field of Data Science using sklearn, pandas, PIL, keras, numpy, scipy, sympy, matplotlib, plotly, seaborn. Also, there are lots of mathematical articles as Jupyter notebooks. 

Library for executing Assembly code with Python using GCC.

Cars detection on parking places using conv2d and xception as base model. 

Keypoints detection in the american football field using heatmaps and unet.

Route time prediction service based LinearRegression with big preprocess of data fitted on data from OSRM and Google.

Route optimization algorithm using greedy algorithm implemented using C++, OpenCl and python.ctypes.

Python library that allows store models topology in text files, not in the souce code. Based on regexps parser and context-free grammar.
- 6 months of experience at Trementum Analytics in the position of Data Scientist and year of experience at university working in the field of deep learning and CPU/GPU calculations. At T.A. I was collecting data using requests and different API's and then I processed it. 

- I was writing educational articles in the field of Data Science on the Code Blog portal. 

- one year of experience at Requestum Software in the Computer Vision field and classical Machine Learning.
I want to impore myself in the Machine Learning field, solve difficualt and interesting problems, work in the team of professionals and get new knowledges in math and computer science at all.
Position: Machine Learning Engineer / Computer Vision
Category: Data Science
Experience: 4 years | English: upper

-Bachelor's degree in Software Engineering
-Exchange student Erasmus+, Belgium
-Prize places in programming contest ACM ICPC (2019, 2020) 1/8 and 1/4
-Top 6% out of 1300 teams in SIIM Covid-19 Detection competition on Kaggle.
I am extremely motivated and self-organized ML/DL Engineer with 2 years of commercial experience. My main interest is Computer Vision. I am also interested in competitive programming and ML competitions.
Projects: 
I have experience with developing data pipelines and model architectures for Object Detection, Keypoints Detection and Classification tasks.
I also have experience with developing computer vision solutions using CV algorithms, OCR and detection methods for automation systems on big factories.
Expect to work with a team on ML, DL, Computer Vision tasks.
Position: Machine Learning Engineer | Computer Vision
Category: Data Science
Experience: 2 years | English: upper


Experienced Machine Learning Engineer in Computer Vision with a mathematical and
software engineering background. Certified TensorFlow Developer. Worked on object detection, segmentation, tracking,
inpainting and style transfer in image and video. Interested in all tasks of machine learning
in computer vison. Excited about bringing new achievements of the AI sphere to everyday
life.

ML Engineer | Computer Vision
Mar 2021 - Present
Impelementing SOTA models in Computer Vision for photo/video editing app. Optimizing
models for on-device inference. Tensorflow and pytorch as main tools for PoC and to
develop solution, CoreML for deployment.
Position: Machine learning engineer, Computer Vision Engineer
Category: Data Science
Experience: 4 years | English: fluent


I have great experience building consumer-focused, practical AIs. My journey in ML started with Natural Language Processing where I invested many hours. After that, I became fascinated by computer vision and deep learning and I am still growing by constant research and building personal projects. I am confident that my knowledge and experience will be an asset to your organization.

Aside from personal projects such as classifiers, spam detectors, and others that helped me enhance my knowledge, my responsibilities in the professional industry have included the development of an e-commerce chatbot for one of the largest companies in my country. Currently, I and our team were responsible for developing word-level sign language detection for the Azerbaijani language which requires deep knowledge of computer vision. Throughout my whole experience, I have developed and implemented various CV models such as AlexNet, ResNets, VGG16, MobileNet, Inception for classification, I3D (Inflated 3D CNN) for action recognition in videos, and object detection models such as YOLO and others. My last project was the implementation of face detection based on the MobileNetV2 model for mobile devices.
Position: Machine Learning Engineer | Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: fluent


I'm a Full Stack Data Scientist / Machine learning Engineer with 3-years of experience providing consulting, Machine Learning software development services. 
I've worked on developing ML for cutting edge fintech startup and helped augment businesses all over the world with machine learning.
I was engaged in R&D department focused on Face ID and developed KYC systems for Indonesian market. 

Given my deep learning experience in research as well as in industry, I have the skills and expertise to take an idea to a production ready and scalable code.

Engineering technologies stack
Docker, Flask, Flask-Socketio, multiprocessing +
multithreading, edge devices integration(Jetson
Nano), Windows integration(pyinstaller), PyQt, etc.

Data Science technologies stack
Pandas, Scikit-learn, XGBoost, LightGMB, Catboost,
Facebook Prophet, model explanation tools(SHAP,
SAGE, eli5, LIME), etc.

Computer Vision technologies stack
Image processing libraries(OpenCV, scikit-image,
etc.), object detection and segmentation
frameworks(YOLO, SSD, Faster R-CNN, Mask R-CNN,
UNET), OCR(Tesseract), etc.

Deep learning technologies stack
Keras, PyTorch, TensorFlow, etc.
Position: Machine Learning Engineer/Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: upper

- 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)
Position: Machine Learning Engineer, Computer Vision Engineer, Applied Scientist, Researcher
Category: Data Science
Experience: 5 years | English: intermediate

- PhD degree in theoretical physics. 
- Participation in the full cycle of development of 3 commercial projects.
- Have scientific publications in refereed journals, as well as participation in international conferences.
5 years of overall experience as Machine Learning engineer in solving complex business problems using machine learning and deep learning techniques. Confident, reliable, proactive team- player, always looking towards improvement and optimal ways to efficient solutions. Constantly strives to increase knowledge and boost learning techniques. Open to new experiences and technologies

Knowledge of classic ML algorithms (Linear regression, Logistic regression, Random Forest, Quantization, etc)

- More than 5 years of experience in the field of Data Science and Machine Learning
- Extensive knowledge of computer science & data structures, ML & DL algorithms, and ML System Design
- Designing and delivering the production-ready DL / ML systems from the scratch
I would like to be responsible for tasks mainly related to the Computer Vision field but a small portion of tasks related to DS areas would be fine. My top priority is a company that seeks a team player for a solid team and projects NOT connected to gambling/bidding/gaming/advertising.
Position: Machine Learning Engineer / Computer Vision Engineer / Data Scientist
Category: Data Science
Experience: 4 years | English: intermediate


Data scientist at PrivatBank 09/2020 - current time
- end-to-end data scientist: EDA, preparing datasets, model training/validating/testing, deployment, monitoring
- Computer vision projects: FaceID (face detection, face recognition, liveness detection), Credit card number recognition, Documents detection and classification, Validation of nude content, sensitive content in images etc.
- No computer vision projects: user's behavioral analytics for Privat24 app, AFS (anti fraud system for p2p)
- Flask web services development
- Model deployment: ONNX, Tensorserver, Torchserver, AWS Sagemaker
- web parsing 

EOS Data Analytics - 1.5 years 
- Experience in processing satellite images (multispectrum, radar), raster and vector data.
 - Experience in data markup and formation of training datasets in formats: CSV, JSON, XML, HDF5.
 - Development of tools for task automation: image classification, object detection, semantic segmentation etc.
 - Experience in unit testing.
 - Technologies, libraries/frameworks: Tensorflow, PyTorch, Keras, Numpy, Pandas, GeoPandas, keras-retinanet, darknet, GDAL etc.

 Trident Defense - 6 months
 - Image/Video processing
 - Development of a mini web application for Raspberry Pi, TinkerBoard, LattePanda (Opencv, Flask)
 - Flask, Django, Docker, MapBox, HTML, CSS