lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Machine Learning engineer
Category: Data Science
Experience: 1.5 years | English: intermediate

Participation in the Startup in robotics, development of logistics robots

I had 2 interesting robotic projects:
- Agricultural robot with elements of computer vision on neural networks
- Robot sapper for humanitarian purposes
Project Manager in BotShare company 07.2020 - 02.2022, 
    Kharkiv (Robotics)
- Preparation and control of the project plan;
- Setting tasks for the project team;
- Managing the priorities of tasks;
- Communication with customers;
- Project analytics;
- Project documentation;
- Preparation of presentation materials.

Embedded developer in BotShare company 09.2019 - 02.2022 
    Kharkiv (Robotics)
- Development and debugging of software for autonomous workж
- Сompilation of algorithms and structural schemes of Software -and Firmwareж
- Вesign of boards, as well as testing and debugging of the test model of the robot;
- Organization of team work;
- Generation of reports;
- Preparation of presentations and demonstrations.

Developer of programs and equipment for automation - Freelance 03.2019 - 09.2021, All Ukraine (Robotics and Automation)
- Development of a "Smart" button to control automated systems. 
- Development of a universal controller for self-service car wash control. 
- Development of a universal analog input board for automation systems.
- Participation in the development of programs and devices for automation of industrial machines;
Develop software and equipment for a robot manipulator for a coffee shop.
I decided that my new path is data science!
I have previously worked with robots and robotics in general, and gained a good background in Python programming, working with hardware, computer vision, understanding the system in general, and much more.
And I decided to try myself in Data Science and did not regret it.
This direction includes many tasks that are very interesting to me. For example, forecasting prices on the stock exchange, the outflow of customers of the company, real estate prices and much more, and this is just working with tables).
But more than that, I want to work with object recognition, detection and tracking, speech recognition, image generation and styling, recommender systems, creating a 3D object from a photo, and much more.
So I have already started my journey and achieved good results.
Now I am looking for a company where I can use and develop my skills. Hope this is your company.

I really want to learn new things and develop in this area, I want to work in a team where I can learn a lot of new things and learn from the experience of others
Position: Machine Learning engineer
Category: Data Science
Experience: 0.5 years | English: fluent


Reinforcement Learning trainee (Python)
Implementing and testing Reinforcement Learning algorithms in different frameworks. 

Researcher in V.N. Karazin Kharkiv National University, Observatory
Computationally modeling the Yarkovsky effect using numerical methods(C++ and Python)
Position: Machine Learning engineer
Category: Data Science
Experience: 5 years | English: upper

#1
Led a team of developers.
Developed system architecture from scratch.
#2
Reduced streaming system latency from 2 sec to 0.5 sec.
Build performance testing infrastructure.
#3
Redesigned NoSQL database schema, migrated huge chunk of data transparently for users.
Software engineer with 5 years of commercial experience (mostly Scala, but also worked with Python, JavaScript). Most of the delivered solutions - high-load, algorithmic, complex systems. 

I have experience in designing and implementing system architecture, leading a team of developers.

ML experience 0.5 years.
Result-oriented and people-oriented management. Open-minded team.
I want to clearly see my role in bringing value to the company, product.
Flexible working schedule. Ability to work not only from the office.
Position: Machine Learning Engineer
Category: Python
Experience: 2 years | English: intermediate

Second place in the international competition Simulink Student Challenge 2018, held by MathWorks (USA) with the work "Humanoid Robot"
03.2023 - Present
Python developer
VisaHQ
Responsibilities:
— development of a chatbot
— ChatGPT integration as an assistant
— research and fine-tuning LM
— development and support of serverless solution

08.2021 - 02.2023
Software engineer in R&D department
LLC KAPELOU
Responsibilities:
— designing the architecture of computer vision systems
— development of computer vision systems
— software integration and debugging
— research work in the field of machine vision
— analysis and improvement of existing computer vision algorithms
— support of implemented solutions

Additional education
Machine Learning
Hillel IT School
Grade: Excellent

Professional skills
— Over 2 years of experience in Python development, knowledge of OOP,
Git and development principles
— Experience in chatbot development, LLM integration (ChatGPT)
— Over 2 years of work with computer vision systems (development,
debugging, integration, support)
— Strong knowledge of OpenCV, Numpy, Pandas, TensorFlow, Keras,
Scikit-learn
— Experience in developing machine learning systems, data markup,
building and training neural networks
— Experience deploying software on Linux, Amazon AWS
— Experience in using C/C++ as an additional language
Position: Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: fluent

1st place in Winter Science Fair, Project: Autonomous Plant Watering system controlled by android (team member). 

2nd place in CanSat Azerbaijan 2019 (Team member)

Computer vision based accomplishments
30% increase in Big Rock (minority) class of AI4Mars Segmentation dataset.

Created powerful Novel Unsupervised Domain Adaptation method to decrease domain gap between sythetic and real dataset.
04/2022 - present
Intern Deep Learning Engineer 
•	Achieved superior result on Semantic Segmentation by applying state of art models and mathematical solutions to overcome challenges of the dataset by improving 30% accuracy on minority class on Convolutional Neural Networks (CNN). 
•	Made research about domain adaptation methods and created novel 3-stage unsupervised domain adaptation mechanism on multi-task learning model. Increased feature extraction capability by using unsupervised learning and self-training over 40%.
•	Increased robustness of the model by 10% with transformer-based architecture

07/2019 – 09/2019
Intern Instrumentation and Control Engineer
•Contributed for factory acceptance test by creating simulation software in C# for safe gas release scheme.
•Corrected mismatching between actual devices in platforms and obsolescence database.

02/2018 – 08/2018
Firmware Developer
•Optimized latency of raspberry by applying firmware corrections (Python) and OS modifications (Linux)
•Created sensor-motor architecture to test designs of mechanical engineers

Additionally from next semester, i am instructor for "AI and ML Fundamentals" course in university in Azerbaijan.
My expectation is to have friendly environment and efficient use of tools to eliminate disadvantages of remote work such as documentation board, agile working and platform for communication. 
Additional technical expectation is cloud access to GPUs
Position: Machine Learning Engineer
Category: Python
Experience: 4 years | English: fluent

- Research on Binarized Neural Networks and Stochastic Computing for 1 year with a doctorate student for my undergraduate thesis, which got me direct entry into the doctorate programme at our university. 
- Built a simple compiler, VM translator and assembler for Jack language, on Hack platform.
- Build an interpreter for Scheme, using Python.
- Udacity Nanodegree in AI Programming
- Executive Data Science Specialization from Coursera
- MTA: Networking Fundamentals from Microsoft
- Deep Learning Specialization
- Machine Learning Specialization
- 1.5 Years as Fullstack Developer and Machine Learning Engineer at Talentra, where I built NLP products, and the platforms on which to deploy them (2018-2020).

- One year on deep learning research (2020-2021).

- Internship as an NLP Engineer and Fullstack Developer at Denebunu (March 2021 - June 2021).
Challenging tasks that allow me to learn new things, and use that to build software with beautiful code and elegant design.
Position: Machine Learning Engineer
Category: Data Science
Experience: 2.5 years | English: upper

1) Took part in the final part of the hackathon and developed a complex system that is able to accurately distinguish and segment as same images of flat or not. Used state-of-the-art models like MobileNet v3, ResNet, CLIP, and YOLOv8 in synergy to get the best score. Placed 5th place out of more than 10 teams;

2) Successfully completed MacPaw Summer Internship 2021 as a Data Science Intern.
1) Building classical Machine Learning models on overly imbalanced data (1: 5000) using the most modern imbalanced learning tools. Effectively serving and building more than 50 models a month. Approaching, model reporting, and communicating with clients.  
2) Efficiently rewrote Pandas data frame preprocessing on Apache Spark, which made preprocessing 3x times faster.
3) Research on current SOTA imbalance learning methods significantly improved the ability of the model to detect the skewed class of the dataset.
4) Currently creating visualization model report with Seaborn, Pandas, and Jinja templates.
5) Worked in a big team of Data Scientists on a model for churn prediction, greatly imbalanced data, and effectively used various tools for dealing with the skewness of classes, which raised the accuracy of the model by 30%.
6) Created a custom template for building machine learning models, that sped up its implementation more than 3 times.
7) Conducted lectures on Machine Learning and Data Storytelling (total number of listeners ~ 150 workers from different departments).
8) Automation of processes with Python, JS, Airflow, SQL databases, Docker, and web-developing tools.
9) Worked, analyzed, and modeled large clusters of data conducting efficient EDA, further target definition, and modeling with various ML models.
10) Fine-tuned RNN for semantic segmentation, used anomaly detection and topic modeling approaches to analyze and process tweets on their emotional color.
11) Utilized the Tableau tool for building efficient reports and presentation skills.
More deep learning utilization preferably in the Computer Vision sphere. More engineering tasks, less Analytics ones. MLops experience and building difficult state-of-the-art models, that will be used in real-world scenarios. Decent financial and social security.
Position: Machine Learning Engineer
Category: Python
Experience: 0.5 years | English: upper


1) NeuroStyle
I've implemented a website where you can apply a selected style to an uploaded image (Neural Style Transfer) using the Flask and tensorflow backend.

2) NeuroBarrier
I have experience in creating a desktop app, which, with the help of a neural network trained by me using YOLOv5 model, recognizes the car and reads the number (using EasyOCR) from it and checks it with the SQL database.

3) My diploma was devoted to the application of graph neural networks (Message Passing Neural Network, Graph Convolutional Network) and Gradient boosting model to determine the error of semi-empirical quantum mechanical methods in determining the relative energy of conformers of biomolecules. Ensemble of model was created, trained and applied to large datasets of biomolecules.
Position: Machine Learning Engineer
Category: Data Science
Experience: 0.5 years | English: pre


1. Researcher in Unicorn Nest
    Gathering data from LInkedIn about key persons of campaigns. 
    Gathering key data from articles about investments. In other 
    words - preparing datasets for neural networks.


2. Trainee Data Scientist  uData School
    Studied in Data Science professional program. 
    Courses completed:
	•	Mathematical analysis 
	•	Linear Algebra
	•	Python
	•	Functional Analysis
	•	Probability theory 

Projects Description:
	•	New York Taxi. We have predicted a price of taxi rides. K-means was used for 
solving a problem with large amount of start and finish points. Linear Regression and 
XGRegression were used for prediction of taxi rides.



3. Teacher of Mathematics
    School of developing mathematics “Interval”
    I teach pupils of grades 1-6. We solve olympiad tasks, play mathematical games.


4. Math Tutor
     Self-Employed
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: upper

- "European Virtual Venture", joint French-Ukrainian  student  program for AI startups development - 1st place
- FUIB Analytics Academy, Data Science - 1st place
2 years as a Data Scientist at First Ukrainian International Bank

Loan default prediction project

A project in currency exchange rate optimization - Time series

Fraud monitoring project

A project for optimizing banking products proposals

Ad-hoc queries for different stakeholders
Adult, gambling
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent

Managed the team of developers along
with coding the solutions hands-on.

Successfully completed several projects:
- engagement rings recommender  (ConvNets, Autoencoders, word2vec); 
- Instagram & Pinterest brand analyzer  (Objects Detection, scraping tools); 
- psychological & motivational chatbot  (Dialogflow, scikit-learn, gensim); 
- job portal recommendation system   (gensim, word2vec, SQL optimization);
- fake content generator   (GPT-2)

Responsible for acquiring new clients,
communicating new projects
requirements.

Created and expanded own Upwork
funnel in the company.

Lecturer of Data Science school
powered by the company
2 years+  experienced Data Science engineer with a demonstrated
history of delivering end-to-end solutions.
Successfully completed several projects related to NLP and Computer Vision.

1 year+ of full-stack web development

1 year as Sales + BDM withing AI industry
Position: Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: fluent


3.5+ year commercial experience as Machine Learning Engineer. Experience with both CV and NLP.
CV projects were connected to object detection, pose estimation, face swap/face alignment.
NLP project were connected with text generation using Gpt2, grammar error correction, NERs.
Several scrapping projects. 
Experience deploying models with Flask.
I would love to work as a Machine Learning engineer. I enjoy programming, so I would like my work to include a lot of it rather than some analysis, and I enjoy thinking about architecture of the final product, and developing algorithms.
Also I would love to work in a friendly team and be able to communicate with them during work as well as after it. 
And I like the idea of work trips, so that I would enjoy if it will be a case.
Position: Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: upper


ANOMALY DETECTION SYSTEM FOR EV CHARGING STATIONS

Built the anomaly detection system to prevent EV charging station failures.
 
Main responsibilities
Data understanding, acquisition of domain knowledge.
Data processing and data visualization.
Generated features for analyzing ev chargers data and modeling. 
Developing unsupervised models.
Analyzing models performance.
Building dashboards to represent the results.

Tools and technologies used:
Languages: Python.
Frameworks: Scikit-learn, NumPy, Seaborn, Matplotlib
Algorithms: PCA, t-SNE Isolation Forest, k-Means, k-Prototypes, DBSCAN, GMM.
Database: MongoDB.

IMPROVING INSURANCE AGENTS’  PHONE NUMBER PERFORMANCE

Built the system to analyze phone number performance and suggest how to use this phone number to achieve the highest contact rate 
 
Main responsibilities
Data understanding, acquisition of domain knowledge.
Data processing and data visualization.
Hypothesis testing 
Statistical modeling
Presenting results in business oriented manner

Tools and technologies used:
Languages: Python.
Frameworks: Scikit-learn, NumPy, Matplotlib, SciPy
Database: Snowflake.

HR TOOL TO MAKE RECOMMENDATIONS FOR USERS

Built the HR tool to make recommendations for users.

 
My main responsibilities were:
Data understanding.
Collecting and processing raw data from the MongoDB. 
Feature engineering.
Developing recommendation engine.
Developing lambda functions.
Analyzing models performance.
 
Tools and technologies used:
Languages: Python.
Libraries: Scikit-learn, SciPy, Seaborn.
Database: MongoDB.
Cloud Services: Google Cloud Platform.
Position: Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: upper

I take part in different hackathons, Kaggle competitions, etc...

I have many pet projects, you can find more info about some of them in my CV, for example:

    I have designed a Military Vehicles Detector Telegram bot that can classify military vehicle using images (in future videos also). I used my own-made custom dataset and YOLOv5/

    I've been working on the NLP task where I was predicting comment toxicity and classification using the BERT pretrained model;
    I was detecting fraud card transactions using contextual feature engineering and unsupervised learning algorithms (especially Isolation Forest);

    I was predicting Dota 2 winner, performing deep feature engineering, 0.846 Accuracy.

    I have the 69th position out of 36 341 in Kaggle House Prices Competition. EDA, Feature Engineering, CatBoost. 

Also, I've passed several courses on Coursera and Stepik, including ones about mathematical statistics, theory of probability, machine learning, Python development, etc, read a bunch of books and so on.

Some of my experience highlights, pet projects, and useful links you can find in my CV and GitHub page.
April 2022 - Now:
  - Machine Learning Engineer at Hopsworks
      * Contributing to the Hopsworks platform - creating DS
        projects-tutorials, writing documentation, testing
      * Modeling using PyTorch, TensorFlow, sklearn
      * Deploying using KServe, W&B

July 2021 - November:
  - Technical Support Specialist at Crassula
    help partners in the configuration of the system, or self-configuration of the product for the client;

Apr 2021 - July 2021:
  - L1 Support Engineer at brightfin
    Take ownership of customer inquiries and issues reported and ensure quick and effective resolution
    Follow standard procedures for proper escalation of unresolved issues to the appropriate internal teams

Jan 2021 - Apr 2021:
  - Application Support Engineer at Thingsboard

Also I am a forth-year student at the National Technical University of Ukraine 'Kyiv Polytechnic Institute', IASA faculty (Data science specialization).
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: intermediate


As a Data Scientist, I have over 2 years of professional experience, specializing in a range of tasks such as data preprocessing, data visualization, prediction, and classification in Natural Language Processing (NLP) tasks. My proficiency in using Python and popular Machine Learning frameworks, such as TensorFlow, PyTorch, and HuggingFace, enables me to perform these tasks effectively. Moreover, I have honed my skills in serving and deploying models through the
use of BentoMl and TorchServe.
I have worked on a number of DL projects, such as:
1) Car Tracker. 
2) Request Parser
3) Face Recognition.

My responsibilities were :
- Collecting And Labeling Data:
- Choosing, implementing, and training the model:
- Converting models from different frameworks:
- Research and propose the model;
- Extend the algorithm (DeepSORT).
- Improve the performance of implemented models.
- Providing a demo.
Position: Machine Learning Engineer
Category: Python
Experience: 4 years | English: upper


As a Machine Learning Engineer, I have a passion for exploring the potential of AI and data science to solve complex problems and create innovative solutions. I bring a strong technical foundation in machine learning algorithms, deep learning frameworks along with a deep understanding of software engineering and cloud-based computing.

I have previously worked for a competitor of Photoshop, where I applied my expertise in artificial intelligence to develop cutting-edge solutions. During my time there, I spearheaded the development of a number of innovative software solutions that leveraged the latest advances in machine learning and computer vision. These solutions helped to streamline various image editing tasks and improve the overall efficiency of the company's operations. It was an exciting opportunity to push the boundaries of what's possible with AI and computer vision, and I'm proud to have been a part of that effort.

In addition to technical skills, I am an excellent communicator and collaborator, with the ability to work closely with cross-functional teams and explain complex technical concepts to non-technical stakeholders. I have a deep commitment to staying up-to-date with the latest advances in machine learning and related fields, and I am always eager to learn new methodologies and technologies to improve my work.

Overall, I am a passionate, detail-oriented Machine Learning Engineer with a strong commitment to using my skills to build AI-driven solutions that can help organizations and individuals achieve their goals.