lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Machine learning engineer
Category: Data Science
Experience: 2 years | English: upper

Bronze Medalist Ukrainian Mathematical Olympiad
Good theoretical background from my bachelors and master allowed me to participate in a number of different, unique projects.
I am interested in Machine Learning Engineering. I have primarily focused on Natural Language Processing, where I have gained experience in developing large language models and utilizing Machine Learning in dialog systems. Additionally, I have worked on recommendation systems based on dialog data.
Position: Machine learning engineer
Category: Data Science
Experience: 4 years | English: fluent


I create machine learning models and retraining systems when needed. Responsibilities vary, depending on the organization, but some common responsibilities my role include: Designing ML systems. Researching and implementing ML algorithms and tools. Selecting appropriate data sets. Picking appropriate data representation methods. Identifying differences in data distribution that affects model performance. Verifying data quality. Transforming and converting data science prototypes. Performing statistical analysis. Running machine learning tests. Using results to improve models. Training and retraining systems when needed. Extending machine learning libraries. Developing machine learning apps according to client requirements.
Machine learning job
Position: Machine learning engineer
Category: Data Science
Experience: 3 years | English: fluent


I have a bachelor's degree in mathematics from Ukrainian university and obtained a Master's degree in Computer Science (Machine learning) from a European university.
At the same time I already have three years of experience in the data science/machine learning domain. I worked on different projects: chatbots, payment classification, recommendation systems, text classification, money laundering detection, debit card fraud detection. Now I am working with computer vision as a machine learning research engineer. My main tasks are model training and evaluation, pipeline optimizations, model inference optimization, preparing models to production, other. I am also the author of several papers (interdisciplinary ones).
Position: Machine learning engineer
Category: Python
Experience: 0 years | English: upper


I have several small projects in machine learning field, particularly on image recognition/object detection using Python, Keras, YOLO. Wrote several mini-projects in C++ (SFML game, Neural network from scratch), had an experience of working in a team on a Django web project.  Am familiar with the basic data structures, principles of OOP. I would like to try myself on a real project and I have a desire to learn.
Position: Machine learning engineer
Category: Data Science
Experience: 3 years | English: fluent


I've been working as ML engineer/Data scientist for about 3 years.  I have experience in various topics that apply Machine Learning: Computer Vision (object detection, segmentation, pose estimation, clothes matching, OCR)
NLP (LLM, chatbots, classification, sentiment analysis, ner, GPT training)
Time series, financial predictions, AutoML
Reinforcement learning, PPO, DQN
High Performance Computing (HPC), horovod
AWS, GCP
MLflow, Airflow, Tensorboard
A little bit of Flask, Django, Streamlit
Position: Machine learning engineer
Category: Data Engineer
Experience: 0 years | English: intermediate

Successfully completed a series of courses at the University of Michigan:
Applied Machine Learning in Python
Applied Plotting, Charting & Data Representation in Python
Applied Text Mining in Python
Capstone: Retrieving, Processing, and Visualizing Data with Python
Introduction to Data Science in Python
Programming for Everybody (Getting Started with Python)
Python Data Structures
Using Python to Access Web Data
I worked for a long time in the field of customs clearance of goods, managed a customs warehouse. Now I am actively studying in the field of machine learning.
Position: Machine learning engineer
Category: Data Science
Experience: 2 years | English: intermediate

- Nova Poshta Innovations Hackathon 2023 1st place
- Developed innovative text/voice assistant. 
- Released AI app on Play Market.
- Adapted transformer model for Android devices. 

- present LLM voice/text assistant
- 30.03.2023 - 30.04.2023 BMW self-driving emergency vehicle light detection.
- 01.12.2022 - 30.03.2023 Bank web service for extracting structured info from images.
- 01.11.2021 - 30.11.2022 Android app powered by NNs for detection, classification, and enhancement of document images.
- 01.03.2022 - 30.04.2022 NLP-based decision maker for advertising placement
- 10.09.2021 - 25.09.2021 Automobiles catalytic converters classifier
- 01.08.2021 - 30.10.2021 Anomalies detection on a production line using an autoencoder.
Last 2 years I've been working with image data as an ML/CV Engineer. This included
- Research and hypothesis definition
- Data Engineering: image data, video, text data
- Model Training: object detection, image classification.
- Model Deployment: creating web service and porting models, creating voice and text assistants based on LLM.
- Model Monitoring and Maintenance: automation pipelines and error analysis.
- Creating an Android app.
- Creating demos and close collaboration with customers 


- Experience with MLflow and W&B
- Experience with CURL, Postman, and Flask
I aspire to be part of a professional team that offers opportunities for both personal growth and project development. I would like to apply all my knowledge and skills to create a meaningful and useful project.
Position: Machine learning engineer
Category: Data Science
Experience: 1 years | English: intermediate

Implemented few ML algorithms:
Image classification (real photos vs unreal/celebrity, people's position classification)
various tasks during online courses and kaggle competitions
Last 5 years I worked with web development (php, python).
First 2 of them as a data analyst
Now I realized that my passion is machine learning.
Mostly I'm interested in computer vision, but I like either as well
My strong side is that I am a backend software engineer. Hence I have enough knowledge to create processes of automated feature extraction, data cleaning, model deployment with docker/kube, etc

I work with:
- pandas, numpy, sklearn, scipy
- matplotlib, seaborn, tensorboard
- tensorflow, keras
- falcon (python micro framework)

I know:
- quite a lot of ML background (Sup/Unsup learning, ensembling, data compression and visualization, etc )
I want to get a position in great team. I'm really excited to work with ML problems, help more experienced colleagues to collect and preprocess a lot of data and gain new experience.
It's really became my passion so i decided to downgrade in seniority and salary
Position: Machine learning engineer
Category: C++
Experience: 5 years | English: upper

Wrote C++ library for real-time video processing from different sources. It also has the ability to stream the result of object detection and tracking and may be used from Python.
Worked on researching an approach for lane detection, which was added to the production pipeline.
Machine learning engineer with experience in real-time traffic analysis and post-processing LIDAR and camera data. Worked on designing and developing multithreaded services for processing IP-camera data by neural networks and other algorithms. Trained and tuned neural networks.
I will not work on gambling project
Position: Machine learning engineer
Category: Data Science
Experience: 2.5 years | English: intermediate


Machine learning engineer with over 2 years of experience, I specialize in the field of speech, specifically in ASR, TTS, VAD and etc. However, I also have a solid understanding of basic NLP techniques and can quickly adapt to other areas such as computer vision and recommendation systems. With a proven track record of designing and building machine learning solutions from scratch. I am passionate about research and enjoy deploying modern models in production environments.
Position: Machine learning engineer
Category: Data Science
Experience: 3 years | English: intermediate


Mar 2020 – Present
RESPONSIBILITIES:
- Design, build and launch efficient and reliable machine learning (ML) services
- Research, develop and expand upon algorithms that will train neural networks to deliver actionable intelligence faster and more effectively
- Develop deep-learning software prototypes that demonstrate potential usefulness to our customers
- Design and develop machine learning systems to create, train and deploy ML models
- Establish reusable data processing pipelines to enable rapid re-training and iteration through different ML methodologies
- Select appropriate datasets and data representation methods
- Design experiments and analysis methodologies that are statistically rigorous
- Perform statistical analysis and fine-tuning using test results
MAIN PROJECTS:
- pose estimation and images classification
- financial trading prediction
Project use new technologies, I`m interested to work with geodata, satellite imaginary and maps and something depended on logistics or urbanism
Position: Machine learning engineer
Category: Data Science
Experience: 0 years | English: upper


M A T H T U T O R
Self-employed
Kharkiv, Ukraine
September 2019 ‐ February 2022
Prepared sample math problems to assess student abilities and
areas needing improvement.
Prepared lesson plans incorporating review, reinforcement and
new mathematics topics.
Educated students by explaining difficult and complex subject
matter in easy-to-understand terminology
Position: Machine learning engineer
Category: Python
Experience: 3 years | English: fluent

Top 300 rated Data scientist on Zindi Africa.
Top 10 in bootcamp hackathon organized by Data science Nigeria.
My name is Agboola Mubarak, I'm a freelance machine learning engineer, I have successfully applied my knowledge across various fields in machine learning with ideologies based from computer vision, natural language processing and recommendation system. I'm time conscious and very efficient in practice.
Position: Machine learning engineer
Category: Data Science
Experience: 0 years | English: intermediate

3 years of struggling with general and theoretical physics. Few Andrew Ng's courses on Coursera.
No previous experience in commercial projects. Currently working on bachelor thesis in applied physics, which includes use of machine learning for recognising patterns in the spectroscopy of the superconducting materials. Also want to incorporate machine learning for classification of superconductors in it.
Find good opportunity to master my skills in programming and data science.
Position: Machine learning engineer
Category: Data Science
Experience: 3 years | English: upper

• developed a distributed system for parameter tuning which received a grant for further development
R&D/Machine learning engineer. I want to evolve towards developing smarter algorithms, keep up to date with the latest research and put them into practice.

• Developed and deployed model for predicting the duration of surgical operations: the project implies discovering non-trivial dependencies affecting the timing and quality of the operations;
improved pre-processing of medical data in teams with surgeons and doctors. 
• Proposed architecture and prepared API for indoor localization: software product that is invariant for sensor types and positioning algorithms. 
• Advanced a novel distributed system for parameter tuning: full-stack development and research.
• Code reviews for quality assurance.
Not interested in e-commerce or gambling projects.
Position: Machine learning engineer
Category: Data Science
Experience: 3 years | English: intermediate


Research of deep learning techniques for action classification. Script's implementation for automatic model training, data processing and video analysis. Spatial and temporal feature extractors (ResNet, MobileNet, RNN, LSTM, MiCT, shallow 3DCNN's) and pose estimation models (Hourglass, HRNet). TensorFlow, Keras, Python, Numpy, PyTorch.
Position: Machine learning engineer
Category: Python
Experience: 1.5 years | English: fluent


Worked on NLP and computer vision projects. Also applied ML algorithms on tabular data and analyzed it using tools like power bi and dash. My last workplace offered me position of middle after 4 months of work.
Position: Machine learning Engineer
Category: Python
Experience: 0 years | English: pre


I am a teacher of physics in college. Working 12 years. Recently completed a machine learning course. I use: tensorflow, pytorch, work with docker. I want to start solving practical problems in machine learning. Of course, I'm more interested in reinforcement learning, but I'm ready to take on any other machine learning tasks
Position: Machine learning Engineer
Category: Data Science
Experience: 3 years | English: intermediate

I have large experience in independent work, organizational skills, time management skills, I also have experience in conducting business, team building, personal management, teamwork.
I have experience in various areas of machine learning: NLP, Computer Vision, Image recognition, searching patterns.
 Also developed data collection controllers in the database(SQL) and processing this data.
My main field of work includes Machine learning, Image and Video processing and recognition, NLP, Data science, Data analysis, BigData and others. I am experienced in developing systems for many business areas, ranging from customers behavior analysis and fraud detection to objects recognition on video.
Position: Machine learning Engineer
Category: Python
Experience: 5 years | English: upper

Winning gold medals in mathematics 2 times among 30 countries
Can speak in English, Russian, Turkish, Azerbaijani very good. Understand French and Germany
Machine learning engineer
• Own, design, and develop AI ML pipelines: be responsible for efficient model training, testing, and monitoring
• Apply scientific knowledge to analyze and collect data, identify problems, devise solutions and construct methodologies
• Develop machine learning and deep learning models for tabular data
• Create and automate data pipelines including data extraction, validation & anomaly detection, indexing, and other data-related tasks
• Use and fit different mathematical and econometric models, develop descriptive and predictive models that deliver better decisions
• Collecting data using scraping tools

AI engineer at E-government Development Center 
• I created the algorithm with the help of OpenCV and applied image processing on the national id cards 
• After successful processing,I created the model with Pytesseract for the specific characters and applied it to the images 
• As the final stage,I built the API which as an input takes the picture of the ID card and returns the information like name, surname, father name, birthplace, birthdate, and id as the JSON file within 2-3 seconds 

Data Science Teacher at Data Scinence academy
• I coached 6 bootcamps in the Data Science Academy as a Teacher and Assistant. 
• As a teacher,I taught the basics of python: types of variables, comprehensions, loops,functions. 
• Scraping with both Scrapy and BeautifulSoup libraries and OOP were also covered in my lessons. 
• I instructed in my lectures the introduction to Data Science with algorithms like Linear and Logistic Regression, Decision Trees, Naive Bayes, kNN, and k-means as well. 

Machine Learning Engineer at Innovation Agency
• In a short time, my job consisted of creation 2 programs as "Sentiment Analyses for Azerbaijan" and "Face Recognition with mask" 
• In the first project,I scraped the data from AppleStore, Google Play, and Facebook, and created nearly more than 80000 sentiments. After preprocessing all the data,I identified the best NLP algorithm among the FastAI, Tensorflow, and PyTorch for this specified case 
• In the next project, "Face Recognition with mask",I learned a lot about the OpenCV library and generated multi-layer perceptron for the face recognition of the person even with mask

Data Science Intern at IKT LAB
• As an intern,I gained lots of experience in the basics of Data Science like Naive Bayes, Regression. During the internship received experience in both Python and excel, also worked with large datasets.
Position: Machine Learning engineer
Category: Data Engineer
Experience: 2 years | English: fluent

• Completed Coursera courses: "Introduction to Deep Learning" and "Neural Networks and Deep Learning", demonstrating my dedication to continuous learning in the AI field.

• Achieved top rankings in hackathons, including 1st place in SmaRTF and 3rd place in NASA Space Challenge
As an Associate Researcher at The Institute for Ethical AI, I'm actively engaged in developing intelligent software solutions using Machine Learning (ML), Deep Learning, and AI. I have experience creating API endpoints for an application and have passion to develop AI/ML models. My work heavily involves Python, where I use libraries like pandas, numpy, seaborn, and matplotlib for data manipulation and visualization, as well as Scikit-learn, TensorFlow 2, and Keras for machine learning tasks.
I expect to work as a Machine Learning / AI engineer. Creating new AI models or deploying existing ones. I could be involved in scientific research in the AI field.

I  do NOT wish to work as an Embedded Engineer.
Position: Machine Learning engineer
Category: Data Science
Experience: 11 years | English: upper

I have relatively popular open source machine learning project on GitHub and wrote a book about Machine Learning with C++.
I have experience in diverse types of projects, mostly based on C++ related technologies. I've worked on game dev projects with computer graphics, various business logic and algorithm development, large code bases maintenance, worked with Chromium browser technology development.

But I want to move into ML and Computer Vision domain where I have lack of experience. The most interesting projects were: developing an application for 3D objects reconstruction based on LIDAR scans, creating a survey and book about machine learning methods available for C++, participating in the background extraction computer vision project, working on an autonomous robot based on Nvidia Jetson Nano that was used for integration of deep learning methods with SLAM algorithm (pet project).

Technical skills:
Languages: C++, Python
IDE/Compiler: gcc, clang, QtCreator, VisualStudio, Eclipse(CDT, ADT), PyCharm
OS: Windows, Linux
Libraries: C++ STL, Boost, OpenMP, TBB, OpenCV, DLib, Numpy, Scipy, PyTorch
Source-Control systems: Subversion, Git
Continuous Integration: TeamCity

Partial experience with:
PyTorch C++ API, MXNet C++ forntend, SharkML, Shogun
I'm not interested in relocation to another Ukrainian city. I don't want to develop UI and work with old legacy code and technologies like COM or MFC. 
I want to participate in a computer vision and machine learning projects. Because of the lack of the commercial experience, I'm ready to work on entry-level tasks, can work on short time projects and preferably part-time.
Position: Machine Learning engineer
Category: Data Science
Experience: 4 years | English: fluent

I was awarded a fully funded scholarship to study for a masters degree in Germany.
**ML engineer:
    -Digging deep into thousands of data records and perform data exploratory analysis
    -Research, prototype, design, implement and evaluate machine learning models for pdf parsing project
    -Perform text classification using BERT
    -Perform image classification located in the pdf documents using Detectron
    -Extract tabular data with the correct extraction order using OpenCV

**Deep learning research assistant:
Reality Gap quantification using Neural Networks and Bayesian inference
    -Doing bayesian modeling and inference: finding tractable approximation of posterior distribution by MGVI
    -Designing model architecture: creating supervised autoencoder
    -Creating the methodology to quantify the reality gap: using Mahalanobis metric as a distance measure
    -Generating synthetic images statistically by sampling from the distribution and by using GANs 

**Data science research assistant:
Ongoing research oriented projects mainly related with medical data such as:
    -Modeling the spread of covid using ODE (ordinary differential equations)
    -Analyzing and visualizing the data provided by different insurance companies

**Data Scientist:
-Create a machine learning model to predict customer churn based on historical data
-Build recommendation system for personalised mobile phone recommendations using web scrapping and ML techniques
-Customer lifetime value prediction

**Data Scientist:
-Developed a text summarization model to automatically generate summaries of large documents
-Use tools like Tensorboard to evaluate the models while being trained
My expectation is to be a part of an innovative team where we can work on ambitious projects by experimenting and learning new technologies while being able to effectively exploit our expertise.
Position: Machine Learning engineer
Category: Data Science
Experience: 5 years | English: upper


- NLP API development for creating goal oriented Chat bots
- semantic search API development
- developing text-to-query model
- developing question answering model for FAQ
- recommendation system development for attributes entitlement
- developing model for trade type prediction
- developing model for request time estimation
- working with large, complex datasets
- difficult problems analysis and investigation, applying advanced analytical methods
- end-to-end analysis that includes data gathering and requirements specification