lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: upper


I live in Mexico. The time difference between Kyiv and Mexico is 9 hours. 

With a strong background in Machine Learning and Natural Language Processing (NLP), I have gained extensive experience in developing advanced systems and models. As a Machine Learning Engineer, and I have successfully worked on recommendation systems, leveraging hybrid approaches such as Wide and Deep, Content-based, and ALS. My expertise extends to handling big data using technologies like PySpark. Additionally, I have contributed to the field of sentiment analysis and emotion detection, developing systems with the help of PyTorch, scikit-learn, transformers, and statsmodels. I experience also encompasses hierarchical classification, where you have designed models to classify and analyze multilingual inputs. I deployed these systems as Docker microservices using the FastAPI library.

In my previous roles, I demonstrated proficiency in tackling various NLP challenges. As a Machine Learning Engineer and Data Scientist, I developed user recommendation systems, scoring mechanisms, and anomaly detection systems using tools such as SQL, PyTorch, scikit-learn, and statsmodels. Moreover, I worked in data parsing and preprocessing for PDF documents and unstructured texts, which involved gathering, processing, and analyzing marketing campaign data. I have expertise in developing text classification, sentiment analysis, text summarization, and emotion detection pipelines using technologies like Pandas, PyTorch, transformers, and statsmodels. Furthermore, I extended my capabilities to the domain of Computer Vision by designing models to retrieve and summarize text chunks, including parsing dates and locations. Throughout my experiences, I have worked with frameworks like Flask, PyTorch, transformers, and statistics to enhance text filtering, classification, and analysis.
I am looking for a long-term stable job with a friendly, open-minded team.  I'm ready for new challenges and interesting projects.
Position: Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: fluent

Implement SoTA white papers months ahead before official code release.
Helped to launch two products.
I'm a ML engineer with strong background in Computer Vision, Deep Learning and 3D domain. For the last four years I've been implementing cutting edge SoTA research papers. This research resulted in the implementation of the key features for two launched products. Apart from production ML, have research experience in NLP and TimeSeries, also familiar with GoogleCloud. 

Tech stack: Python, PyTorch, Keras, tensorflow, numpy, matplolib, scipy, pandas, DVC, Docker, GIT, OpenCV, C++, CUDA, GCP
Position: Machine Learning Engineer
Category: Data Science
Experience: 7 years | English: upper


I'm an engineer with 7+ years of experience in Data Science and Software development.

Education:
- PhD student in Computer Science
- MS in Intelligent Data Analysis with Honors

Skills and experience:
- Knowledge of statistics, linear algebra and mathematical analysis;
- Research mentality and math-oriented mindset;
- Good presentation/communication skills;
- Leadership and mentorship skills;
- Experience in project management, including DS projects;
- Knowledge and understanding of OOP concepts;
- Participation in the testing process through test review and analysis;
- Experience with machine learning/data science and deep learning methods, techniques and algorithms;
- Experience in deep learning models’ training, fine-tuning, optimization and inference process;
- Languages: Python, JavaScript, C/C++, C#, MATLAB, R;
- Frameworks and libraries: numba, scikit-learn, pandas, TensorFlow, Keras, PyTorch, TensorRT, Triton inference server, ONNX, NNAPI, OpenVINO, OpenCV, LightGBM, etc.;
- Experience with Google Cloud Platform, Amazon Web Services;
- Experience with Big Data: Kafka, Hadoop, Hive, Spark, Airflow, NiFi;
- Containerization tools: Docker.

Projects:
I participated in whole project development stages from presale and roadmap construction to ending project deployment, integration, and support.

Roles: 
Computer vision engineer, AI/ML engineer, team lead, python developer, articles writer and proofreader.

Responsibilities: 
Models development, tuning, optimization and integration, pipeline development and optimization, architecture design, backlog planning, reporting, and communication with stakeholders and clients.

My past projects mostly were related with 
- computer vision: object detection, segmentation, tracking, image processing;
- signal processing: filtration, smoothing, forecasting, recognition;
- classical data science like classification and regression.

Also, I have experience in different domains: retail, agritech, sport, telecom, automotive, GIS.
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: upper


Implemented optimization algorithms to production. 

Implemented fuzzy-logic reasoner to reconstruct unstructured data.

Fascinated by Data Engineering and deploying models to production. Would like to work with Cloud technologies (GCP, AWS)
Position: Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: fluent

- Led the development of a GAN model for floor plans, resulting in realistic and diverse floor plan layouts.

- Increased company revenue by 15% through the automation of critical business processes using custom DS/ML technologies.

- Designed and implemented a Super Resolution model to upscale low-resolution images, improving the quality of visuals for customers.

- Proficient in Python, AWS, Pytorch, OpenCV, PostgreSQL, Gitlab CI/CD, Docker, k8s, MLFlow, xgboost, and other cutting-edge technologies.

- Analyzed borrower profiles, optimizing lending strategies with data-driven insights.

- Formulated and maintained a hypothesis-driven approach for personalized client recommendations, resulting in increased satisfaction and loyalty.

- Led the development of the SuperApp Recommendation System, driving innovation and growth with business logic and architecture.

- Won the 1st place in Datathon with project for UNICEF.
In my previous experiences (3 years), I have completed various projects and tasks utilizing cutting-edge technologies such as Python, AWS, Pytorch, OpenCV, PostgreSQL, Gitlab CI/CD, Docker, k8s, MLFlow, and xgboost. I strive to continuously improve my skills and stay up-to-date with the latest industry trends to deliver high-quality results in any ML-related role I take on.
Interesting projects. Currently keen on NLU/NLP and CV tasks 🫶
Position: Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: upper

1) Graduated from Karpov's Data Analyst courses. During the course I learned:
- Properly handle data
- Use Python for data analysis (pandas, numpy, matplotlib, seaborn)
- Compose queries in ClickHouse and PostgreSQL
- Based on the results of A / B testing, draw conclusions about the best version of the product
- Basic concepts of probability theory, conducting statistical tests
2) Completed a course on the basics of Python on Stepic
3) Graduated from the OOP Python course on Stepic
4) Graduated from the Deep Learning Specialization from Deeplearning.ai on Coursera
I started my career teaching mathematics. I prepared applicants for admission to universities.
After graduating I stayed to work at my university in the teaching and methodological department.
During quarantine, I simultaneously worked as a business analyst in the "E- Prosecutor" project for the Azerbaijani prosecutor's office. My tasks were:
1) Interaction with the client and obtaining information about the project from him
2) Analysis of the project workflow
3) Development of the project structure
4) Preparation and writing of a technical document of the developed program
5) Designing project modules
6) Testing the developed program

Further, I became interested in the field of machine learning. To develop in this area, I take various courses on educational platforms such as Stepic, Coursera, as well as on various Youtube channels.
I like machine learning because I can apply my mathematical knowledge in parallel with programming. I'm interested in what's "under the hood" of machine learning algorithms, as it will help me to apply models intelligently to solve future problems.
Python is a good tool for this. Therefore, I focused on studying this particular programming language: on the study of data structures and algorithms, as well as on object-oriented programming.
Position: Machine Learning Engineer
Category: Data Science
Experience: 7 years | English: upper

Worked in different fields with product companies and know how to get interesting insights that will bring business value to your company!
I've worked on a wide variety of projects associated with human interactions and behaviour. Interested in similar projects and open for new horizons.
Machine Learning, Python, SQL,
 Spark, Big Data
Cassandra, Redshift, PostgreSQL,
AWS SageMaker
Big amounts of data, interesting analytic tasks.
Will be a plus: big DS team
Position: Machine Learning Engineer
Category: Data Science
Experience: 4 years | English: upper

Published two research papers and one research summary.
Received eight scholarships during my studies.
Won second place in international IT competition
Attended several data science and software programming hackathons
I worked on an NLP project, fraud detection, credit scoring, CRM models in the banking industry using Python and its machine learning libraries (Keras, Scikit-Learn, TensorFlow, Gensim). Besides, as a data scientist, I started data governance procedures, implemented automatic data quality measurements in the insurance industry, and developed a pricing model for casco insurance.
Position: Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: upper

I was enabled for new unique and robust solution for CV and NLP.
I worked with Computer Vision project.
The project was to develop a model or a several models,
which would identify available dates in Calendar applications.
I`ve passed the full pipeline: data preparation;
data augmentation; training, deploying.
I work with scraping datasets and preprocessing for NLP
Next Word Recognition project.
I have 2 years of experience in the position of
Machine Learning Engineer.
To obtain new experience in Machine Learning sphere.
I am looking for a company that will enable me to processes and bring to me new challenges.
Position: Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: intermediate


Last job at Datagrok as a Data Scientist(more info in the CV):
- Creates software products related to data processing, statistical calculations for a
US-based Fortune 500 pharmaceutical company;
- Works on the module of interaction with databases;
- Works on a package for platform interaction with machine learning;
- Improves the core of the platform for data processing and visualization;
Position: Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: pre

python, numpy, pandas, docker
seaborn, scikit-learn, matplotlib
xgboost, logistic, linear, SVM
understanding of the basic machine learning algorithms, the process of working and training neural networks, preparing and cleaning data. knowledge of optimization and parameter tuning. Understanding of mathematics and calculus.
# Machine Learning (Coursera, Stanford)
# Specialization Deep Learning (Coursera)
 -- Neural Networks and Deep Learning
 -- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
 -- Structuring Machine Learning Projects
 -- Convolutional Neural Networks (in process)
# Exploratory Data Analysis for Machine Learning (Coursera, IBM)
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent

• Certificate about participating in the Final stage of IDAO (International Data Analysis Olympiad) held by Yandex LLC, Moscow. Top 30 among the 1000 teams.
• Award of Achievement for successfully completing the Oracle Academy "Database Design and Programming with SQL”.
• Deep Learning Specialization Certificate offered by Coursera, Deeplearning.AI
Machine Learning Engineer, master's student at the University of Padua, Italy in ICT.

I'm quite interested in working on images utilizing Computer Vision and Deep Learning. Currently, I'm conducting research about detecting anomalies in data coming from smart health devices using Machine Learning techniques.

Education:
- Bachelor's degree in Computer Engineering, ADA University, Baku, Azerbaijan.
- Master's degree in ICT, University of Padua, Italy.

Past experiences:
- Machine Learning Engineer
Desion GmBH, Darmstadt, Germany.
(November 2021 – June 2022)
• Utilizing Keras, Tensorflow, and Pytorch frameworks to build Deep Learning models.
• Solving Image Classification, Object Detection and Localization types of Computer Vision problems.
• Built a web scraper and scraped around 200k images from the various websites.
• Developed Python/Bash scripts to clean and manage the raw dataset, and transform it to COCO, Pascal VOC data formats.
• Utilized the Detectron2 framework for object detection tasks with two-stage architectures (Faster R-CNN, Mask R-CNN).
• Utilized the Keras framework for classification tasks with one-stage architectures (VGG, ResNet, EfficientNet).
• Implemented different techniques to evaluate the performance of the trained networks such as item similarity based on Top-N recommendation.
• Utilized KerasTuner and RayTuner hyperparameter search
frameworks for hyperparameter tuning. Deep dive into the Bayesian hyperparameter optimization.
• Set up and further improve the data pipeline, and implement data augmentation with Tensorflow Data API.
• Built a REST API using Flask that handles user login, registration, and authentication with JWTs, accepts images from the user side, and returns the model prediction 
• Read research papers about the novel network architectures and implemented them in Keras.
• Worked with SQL to manage the user-related data in REST API and embeddings from the trained networks over images for the recommendation system.

Software Engineer Intern
Mobisec Italia Srl, Treviso, Italy
(March 2021 – May 2021)
• Development of Automated Security Tool.
• Automation of the "Dry-run" process which checks the vulnerabilities present in the mobile application on a surface level.
• Utilizing Machine Learning to detect false/positive results from the "MobSF" platform.
• Applying Convolutional Neural Networks (CNNs) to automate the detection of UI fields.
• Using "Appium" to automate UI processes.
Position: Machine Learning Engineer
Category: Data Science
Experience: 1 years | English: intermediate

1. Spotify Lyrics analysis, explicit content identifier using simple tf-idf and Random Forest algorithm
2. Stylometry research
Machine Learning Engineer with 1 year of the overall experience. My responsibilities were focused on prototyping new or improving existed models:
- Natural Language Processing (classification, sentiment analysis, NER, Text Generator using GPT-2, Summarisation)
- Worked with classic Machine Learning Models (Random Forests, XGBoost, Scikit-Learns )
- Experience in deep learning - used pre-trained models, custom architectures and loss functions construction
- Experience with unsupervised methods, clusterization and anomaly detection
- Able to cover cycle — data analysis, research and development, feature engineering, testing and deploying to the production
- Able to work both myself and in the team
Preferably, I want to become a part of professional command in NLP product/projects/researches.

Interesting and non-trivial tasks in machine learning and deep learning;
Flexible working schedule;
Remote working possibility;

NOT data engineering;
Position: Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: fluent


Machine learning engineer with 3 years of experience in practical machine learning, natural language processing, and data mining. Excited about building, deploying, and maintaining effective machine learning solutions that cater to business needs.

Proficient in Python and familiar with other programming languages. Have experience in data analysis, cleaning, and visualization using pandas, SQL, ElasticSearch, PySpark & Databricks, matplotlib, seaborn, plotly, etc. Well-versed in machine learning algorithms, deep learning, NLP, and graph machine learning, utilizing tools such as scikit-learn, XGBoost, PyTorch, TensorFlow/Keras, NLTK, Stanza, Transformers, OpenCV, PyG, and DGL.

Have experience working with cloud computing and services platforms, specifically AWS. Familiar with MLOps and AutoML principles.
Position: Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: fluent


Machine Learning Engineer with 3+ years of experience specializing in developing ML solutions from scratch and adapting existing ones to the customer use-cases.

- Adapted and developed an unsupervised DL model for circuit board anomaly detection
- Performed data engineering and maintained Jenkins automatic testing and training workflow
- Invented the multi-task color image quantization and clusterization approach using the classical computer vision segmentation algorithms
- Developed and deployed a supervised DL segmentation model for determination of the risk of plasma leakage from the magnetic installation
- Researched and developed an end-to-end DL pipeline for deblurring model to restore photo quality
- Increased FPS number for the existed SOTA approaches while preserving the same accuracy by changing the model architecture and applying quantization
- Made the model robust to distortions, e.g., noise, space transformations, motion blur
Position: Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: upper

- Master degree in Data Science
- Worked with GANs in my Master Thesis, have a strong mathematical and practical understanding of the field
Machine Learning Engineer with 5 years of the overall experience. Through different projects and working in few companies, my responsibilities were focused on prototyping new or improving existed artificial intelligence models:
- Worked with classic Machine Learning Models (Random Forests, XGBoost, Scikit-Learn, Nvidia RAPIDs)
- Experience in deep learning - used pre-trained models, custom architectures and loss functions construction
- Experience in the Image Classification, Object Detection, Object Tracking, Instance and Semantic Segmentation, 
- Experience with Deep Generative Networks (GANs, VAE)
- Experience with unsupervised methods, united it with supervised methods
- Worked with classic Computer Vision (Object tracking)
- Able to cover full data science cycle — data collection, research and development, feature engineering, testing and deploying to the production 
- Able to work both myself and in the team
- Experience working in an international team
Interesting and non-trivial tasks in machine learning, computer vision and deep learning;
Flexible working schedule;
Remote working possibility;

NOT data engineering;
Position: Machine Learning Engineer
Category: Data Science
Experience: 6 years | English: upper


Machine learning engineer with deep knowledge in theoretical and practical machine learning and experience in managing middle-size groups of researchers and engineers.

- Graduated from Moscow State University and Yandex School of Data Analysis
- Successful at competitive data analysis (Kaggle Top 14 Global) and mathematics (Asian Pacific Math Olympiad, bronze medal)
- Recent experience mostly around computer vision: classification, segmentation, detection, tracking, and re-identification for healthcare and retail companies
- Previous experience in classical machine learning, recommendations, and time series prediction.
- Mostly python stack of technologies
- For deep learning more proficient with Pytorch, but also had some experience working with TensorFlow
- Founded a Kazakhstan data science/machine learning community with a learning resources archive, mentoring program, offline/online meetups, and a job board.
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent


Machine learning Engineer with experience in Deep Learning, NLP and CV.
Worked with feature engineering and Big Data
Master`s degree in computer science.
Feel free to ask for my CV&Contacts for more information
Position: Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: fluent

TensowFlow Developer - Google:
Examination Areas: Integrating Machine Learning with time series, computer vision, convolutional networks, and natural language processing. EXAM SCORE: 24/25

Machine Learning Specialization - Stanford University/ DeepLearning.AI (via Coursera)

Deep Learning Specialization - DeepLearning.AI (via Coursera)

TensorFlow Developer Specialization- DeepLearning.AI (via Coursera)
Machine Learning Engineer with multi-disciplinary engineering background and strong research aptitude. 
Google Certified TensorFlow Developer. 

M.Sc. in Computer Engineering / Data Science from top European Engineering School.
B.Sc. in IT and Systems Engineering from top engineering school in the country  

Looking for applying state-of-art deep learning applications to help businesses advance

Well-versed in various Machine Learning fields e.g. Supervised/Unsupervised ML, Deep/Shallow Learning, Reinforcement Learning techniques.

Proficiency in Computer Vision, NLP, Time Series applications.

--- ML Engineer (2023)
•  Sole Machine Learning Engineer on team, 
•  Leading creation of custom datasets, developing ML algorithms using advanced NLP techniques
•  Contributing to early development plans for ML models.

--- First data scientist** in country`s largest online payment company (2017)
• Researched on applications of data science methodologies to help the company to grow.
• Processed data on overall sales/revenues of the company. 
• Calculated association rules on sale channels/products and built forecasting models etc. 
• Main tools used: Python, Excel, and R.
      ** in intern capacity

--- Flight Dynamics Intern at regions only satellite operator (2016)
• Assisted Flight Dynamics group members.
• Office was responsible for overseeing satellites` orbital parameters, station-keeping operations and general wellbeing of satellites
Position: Machine Learning Engineer
Category: Data Science
Experience: 1.5 years | English: fluent


Machine Learning Engineer with over one year of experience in the IT field. I have a background in developing language models, implementing gesture recognition algorithms, and building object detection and segmentation models. Proficient in Python, SQL, and Microsoft Azure.

Completed projects:
• Implemented a kick gesture detection and classification model for hands-free trunk opening. Developed Activity Recognition Performance Metrics for efficient error analysis.
• Implemented a bacteria detection algorithm using YOLOv5 object detection model on NVIDIA Jetson Nano.
• Developed an instance segmentation model to detect, classify, and segment breast tumors from mammographic X-RAY images employing CNN-based models such as ResNet-22, Faster R-CNN, and Mask R-CNN.