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

Achieved Data Scientist Professional Certificate from Datacamp. Accomplished 100+ 4-hour Datacamp courses on several DS topics, from Importing Data to Model Fitting and Model Evaluation, get acquainted with several ML Models, solved several DS problems (Regression, Classification, Clustering). Completed many Career Tracks from DataCamp: Data Scientist with Python, Data Analyst with Python, Analyst with SQL Server.
Have finished DataQuest 240+ hours Data Scientist with Python Career Track and additionally have finished 365DataScience Data Scientist Career Path, have learned many crucial Data Science topics, such as Statistics and Probability, Linear Algebra, SQL, ML, Deep Learning.
Have proven commercial experience in various ML domains, from Risk Modelling and Recommendation Systems to Object Detection and Image Classification.

Tech Stack: Python, PyTorch, OpenCV, PIL, Streamlit, Pandas, Numpy, Seaborn, Plotly, SciPy, Scikit-learn, Imblearn, LGBM, XGB, CatBoost, Cornac, Implicit, LightFM, recommenders, H2O, Optuna, STEGO, YOLO, T-SQL, R(dplyr, ggplot2, data.table).

Data Science & Miscellaneous Technologies: Data science pipeline (cleaning, manipulating,visualization, modeling, interpretation, deployment), Statistics, Hypothesis Testing, Confidence Intervals, OOP, Git, Tableau, AWS S3/Lambda/EC2/CLoudWatch/SNS
Position: machine learning expert, AI researcher
Category: Data Science
Experience: 5 years | English: upper


- Implemented Medical disease diagnosis system using Natural Language Processing 3 years ago
- Finished Traffic simulation system design and programming based on python 2 years ago
- Managed and designed research and analysis to improve business performance across and within 7 departments
- Built 36+logical models and worked with database administrators to understand and develop physical models and overall data architecture for 5 years
- Leveraged big data to discover patterns and solve strategic analytic business problems
- Implemented object detection system from video in real-time
Position: Machine Learning Intern
Category: Data Science
Experience: 0 years | English: fluent

Not much of an achievement, but I am proud to be a student at UCU - a prestigious university famous for its high standards and amazing community. That took quite a bit of effort on my part.
Worked as a research intern at Ukrainian Catholic University ML lab on a joint project with Softserve, June-October 2021. My responsibilities were to conduct approved experiments with the dataset provided, then visualize and present results. Examples of my tasks: run the dataset videos through a face landmark detector, record coordinates, analyze motion; visualize errors relative to ground truth data; run the dataset through a pre-trained neural network, visualize attention masks; analyze the current baseline algorithm, add a new step - a custom motion detector etc. Visualization had always been my strongest suit and also my favourite, I am rather creative when it comes to comprehensively illustrating everything and anything that happens to the data.
I would like to work either as a data science intern, assisting with the responsibilities of REAL data scientists or work with data visualization (which is arguably my strongest skill). Will also consider being a Junior Python Developer.
Position: Machine Learning Internship
Category: Data Science
Experience: 8 years | English: fluent


•	Start-Up operation 
•	FINTech Include Forex, Binary and Crypto
•	Call center 
•	Sales & Marketing 
•	Finance and Budgeting 
•	English, Arabic & Russian
•	IT development and system integration ML and AI enthusiastic
Position: Machine Learning Manager
Category: Data Science
Experience: 3 years | English: fluent

Doing ML project about sports predictions
MS in Statistics
Codewars python - 4kyu
- 1 year experience in a leading product IT company in London as a Data Scientist
- 3 years experience in a leading product IT company in Kyiv as a Data Scientist
- 1.5 years of work experience in a huge German company in their Kyiv office (Operations Planning Manager / Data Analyst)
- Internship as Risk Management intern in Germany
- 2 years of doing my own project in Football Predictive Model from scratch (collecting data in web (more than 250K matches with a bunch of features, data cleaning, creating DB, creating successful models by using Machine Learning methods)

Hard skills: Python: pandas,  sklearn, TensoFlow (basics), Keras, numpy, BeautifulSoap,requests, SQL, Machine Learning, Statistical background
Coursera completed courses: Deep Learning Specialization, Applied Machine Learning with Python
Looking for the interesting ML project to create real ML and deep learning models and to solve problems by using these methods.
Position: Machine Learning / MLOPS Engineer
Category: Data Science
Experience: 5 years | English: upper

Applied mathematic master degree: optimisation, probability theory and statistic, numerical methods, control theory.

Extremely qualified in deep learning and have experience with different solutions for common problems: imbalanced datasets, overfitting, gradient vanishing. 

Computer vision: Worked with state of the art architectures for object classification, detection, instance and semantic segmentations: EffNet, ResNet, Unet, Mask-R-CNN.

NLP: Worked with GLOVE and Transformer based models for text classification, NER, similarity recognition.

Designed and deployed a vast amount of custom architectures for  different domains: CNN; LSTM; RNN; Attention; mixed image, text and table inputs. 

Experimented with variational, graph and fast CNN models. 

Experienced in various classical machine learning techniques (SVM, DTC, PCA, TSNE, Bayesian models)

Certificates:

2020
Data Engineer Nanodegree
2019
Advanced Machine Learning with TensorFlow on GCP
Data Engineering on GCP
From Data to Insights with GCP
2018
Self-Driven Car Engineer Nanodegree
2017 
Machine Learning Engineer Nanodegree
Results:

2021-2022:

Deployed several TF extended pipelines for automative model training conveyors via Kubeflow on Premise and on GCP and Airflow. 

Trained, modified and deployed (async http, docker):

- several models with transformer architecture for name entity recognition. 
- image classification and model with Effective CNN as a backbone 
  model.
- adverts and texts similarity classification models. 
- MaskRCNN for watermarks detection. 

I was responsible for full process of model development: 

- EDA
- experiments with different model architectures 
- deployment
- worked closely with data moderation team for model validation 
   before deployment. I also developed datasets for model training 
   and improvement.  

2020 - 2021:

- customer clusterization models improvement and deployment via 
  AWS Sagemaker and Glue.
- OCR models based on variational multitask autoencoder 
   architecture.
- RNN model for estimating crop yields via satellite images of 
   vegetation indexes.  

2018-2020:

Responsible for full process of deep learning research and deployment of different models:

- advert categories classification based on texts and images neural 
  networks. Deployed them via TF Serving.
- various deep and bayesian models for marketing fraud detection: 
  TTI-injection, spam, bots. 
- scam detector based on user experience and advert metrics. 
  Worked with downscaling, upscaling, weighting due to a high 
  imbalance of dataset.
- CTR predictor of adverts based on attributes, content, prices, and 
  regions. Worked with GLOVE embedding, and custom loss 
  functions. 
- U-NET autoencoder for finding texts on images.

Android developer: 2013 - 2018.
Position: Machine Learning / Mobile Developer
Category: Data Science
Experience: 5 years | English: fluent

Machine learning since 2014 and iOS since 2012.
Overall 5 years of experience in software development.
Expertise in machine learning, Python, R, mobile development (iOS), natural language processing, deep learning, version management systems, unit tests and test automation, data visualization and analysis, Agile/Scrum.
Fast learner, self-starter, adaptive, self-organized, open source contributor. I like to share knowledge.
I'm interested in projects related to one or more things from this list: Machine Learning, Deep Learning, Data Science, AI, Natural Language Processing, Bioinformatics, Healthcare, Biotech, R&D.

Not interested in propositions related to eCommerce, Ad, Gambling, Social Networks, Banking.
Position: Machine Learning/ NLP Engineer
Category: Data Science
Experience: 5 years | English: upper


-Collaborated with a team of developers to build OpenAI models for natural language processing and image recognition.
-Utilized Node.JS and React to build web applications that integrated with OpenAI models.
-Built custom API endpoints to expose OpenAI models to third-party applications.
-Conducted performance testing and optimization on OpenAI models to improve accuracy and efficiency.
Worked closely with clients to understand their needs and provide technical solutions that meet their requirements.
Position: Machine Learning/Prompt/Deep Learning
Category: Python
Experience: 5 years | English: fluent


I have completed full master of science coursework in Data and Decision Science masters on Deep and Machine Learning. I am a chemical engineer and Physicist. I worked as a Physicist Data Analyst at CERN on behalf of University of Liverpool. I am a fast learner and can complete multiple projects at short periods with excellence. I am competent in many divisions of Computational Sciences + Physics, Chemistry and Mathematics
Position: Machine Learning Research engineer
Category: Data Science
Experience: 4 years | English: upper

Master's student of UKU ( Data Science )
Work on R&D AI/ML projects. In my portfolio, I mostly worked on computer vision projects, but also in the field of finance, NLP and others.
Position: Machine Learning / Research Engineer
Category: Data Science
Experience: 2.5 years | English: fluent

- Earned Bachelor's degree in applied mathematics and informatics.   
- Completed "Machine Learning" course on Coursera.  
- Pursuing an MSc in Data Science degree (estimated graduation Jan 2019).
- 2.5+ years of commercial experience working as a Software Engineer on Big Data project with cutting-edge technologies.  

Software Engineering skills:
- Python (Flask), SQL, Cassandra, Linux, Docker, Git.  
- Have some experience with Java, Scala.  

Machine Learning skills:
- Python (NumPy, Pandas, Scikit-Learn, Keras, Matplotlib, NLTK).  
- Understanding and experience with common Machine Learning & Deep Learning methods.  
- Strong mathematical background (Linear Algebra, Statistics, Calculus).
Looking for data science / machine learning / research positions (preferably in Computer Vision).
Position: Machine Learning Research Engineer
Category: Data Science
Experience: 5 years | English: fluent


Created image2image super resolution and restoration framework used by ~2M users and dozens of b2b customers. Work with GANs and image2image networks. Research, implement, train and deliver into production neural networks in computer vision area. Frameworks: Tensorflow/Keras, Pytorch. Python ML stack: numpy, scipy, sklearn, OpenCV.
Position: Machine Learning Research Engineer
Category: Data Science
Experience: 2.5 years | English: fluent


For the last two years, I've been doing research in computer vision with a focus on generative AI. Most recently, I worked in R&D as an ML research engineer. My job was to build a tool for 3D content creators. Besides computer vision, I have a thorough understanding of machine learning as a field and a keen interest in reinforcement learning. Additionally, I am a quick learner and can easily adapt to new business domains. My tech stack includes the usual ML frameworks and tools (PyTorch, Tensorflow, Lightning, Hydra, Numpy, etc.), and I have ample experience training large models (1B+ parameters) on multi-GPU servers.
Position: Machine Learning Research Engineer
Category: Python
Experience: 3 years | English: intermediate

Projects:
1. Developed boots type recognition system using CNN (fine-tuning).
2. Developed sentimental analysis system using LSTM and Convolutional Nets;
3. Developed time-series prediction system using Recurrent Neural Networks (LSTM);
4. Supporting face recognition server;

Completed online courses:
1. Machine learning course  – Stanford University, Andrew Ng, Coursera.
2. Neural networks for machine learning – Toronto University, Geoffrey Hinton, Coursera.
3. CS231n: Convolutional Neural Networks for Visual Recognition – Stanford University, Fei-Fei Li, Andrej Karpathy, Justin Jonson.
Programming languages: Python, Java, C#, C++, C.

Libraries and technologies: Numpy, SciPy, Keras, Pandas, UnityEngine, RegExp, Qt, JSON, XML, Git, Tortoise SVN, ZeroMQ.

Familiar with: OOP, Design Patterns, Caffe, Theano, CUDA, Matlab, SQL, OpenCV, Android SDK, boost.

Deep learning: MLP, CNNs, RNN (LSTM, GRU), Back-propagation algorithm, optimization and regularization algorithms, data augmentationm, backprop to image, etc.

Commercial experience:
Software Engineer - 2 years.
Machine Learning Engineer - 0.5+ years.
My research interests lie mostly in computer vision problem - object recognition, detection, scene understanding, etc. Also, I'm very curious about reinforcement learning fields, robotics and other AI related fields.

Not very interested in projects related to ads.
Position: Machine learning researcher
Category: Data Science
Experience: 3 years | English: upper


Proficient in deep learning for Computer Vision applications. Worked on following tasks: 
- Single image super-resolution
- Image artifact removal
- Style transfer
- Aesthetic image classification
- Multi-label classification
- Object detection
- Tracking
- Segmentation
- Few-shot learning
Position: Machine Learning Researcher
Category: Python
Experience: 1.5 years | English: fluent

Currently I'm working on developing algorithms to automatically adjust neural network parameters.
I'm continuously learning various algorithms for performing supervised and unsupervised learning with neural networks, SVMs and decision trees. I'm independent of specific tools, libraries and languages -- this year I was mostly working with python (numpy, scipy, sci-kit, theano, pylearn2, ...).
I am willing to participate in innovative research projects with Machine Learning applications. My primary goal is to establish a knowledge exchange on a continuous basis, however I expect the company to have a transparent management with the ability for employees to influence the business decisions.
Position: machine learning researcher, data scientist
Category: Data Science
Experience: 5 years | English: intermediate

Building from scratch a profitable trading model based on a neural networks for trading on a cryptocurrency exchange. From data collection to deployment and automatic continuous retraining.
As a Data Scientist and ML Researcher/Engineer I worked on time series analysis, predictions, feature engineering, built and trained neural network models with multiple GPUs, worked with reinforcement learning, created my own hybrid learning system with elements of both reinforcement learning and self-supervised learning, built a continuous automatic retraining system,  and deployed my models for production on remote servers. Also worked on testing of hypotheses, linear model building, factor analysis and search for a causation direction.

I am a former experimental physicist. I have extensive experience in the manufacturing business. From 2014 to 2017, I was engaged in statistical testing of psychological rehabilitation methods. Since 2017, I have been working in an IT company primarily on finding profitable trading models on cryptocurrency exchanges. I also solved some tasks related to the analysis of e-commerce data.
significant research component
Position: Machine Learning Researcher / Engineer
Category: Data Science
Experience: 7 years | English: upper

Courses:
• Introduction to BigData and Hadoop - Course by QALight
• Molecular Biology of the Cell - Stepik
• Big data & Genes - Coursera
• Computational Neuroscience  - Coursera
Passionate in such fields as computational neuroscience and machine learning.
I like to solve an interesting and challenging tasks with my expertise in machine learning and analytical approaches. 
I have experience with implementing ML models and data science research in variety of the different fields such as e-commerce, cybersports, bioinformatics and mental health.
• Digital Signal Processing (DSP)
• Computer Vision
• NLP
• BioMedical Image Processing
• Researcher 
• Software developer
I'm interested in Brain–computer interface, biotech, healthcare, computational science technologies.

I'm NOT interested in e-commerce, fintech, retail, marketing.
Position: Machine Learning Researcher, Machine Learning Engineering
Category: Data Science
Experience: 4 years | English: fluent

PhD degree, solved interdisciplinary problem from Quantum Engineering and Applied Maths. Developed pioneering algorithms on that. .
5 years of software development experience in a US-based technological corporation, focusing on scientific computing and numerical algorithms R&D. This includes literature survey, algorithms prototyping, hypotheses checks, as well as the development of unique numerical algorithms from scratch. Programming languages used: Wolfram Language and Python.
Also have a PhD degree in Applied Maths/Physics.
Looking for Machine Learning Engineer roles, my goal is to shift from the development of numerical algorithms to ML.
Position: Machine Learning Researcher, Project Leader
Category: Python
Experience: 8 years | English: upper


Hi! My name is Dmytro.
I'm a project leader with 2 years and research engineer with 7 years of experience in the AI R&D. For the last two years I've been leading a project on the intersection of AI and cybersecurity which is successfully integrated into the production. My experience covers multiple AI fields including CV, NLP, Meta-learning, AI security, anomaly detection and classical machine learning. 
Besides my direct engineering background, I have experience in patent preparation (USA, Korea) and publication preparation. 
Before direct leadership of the project, I've been a tech leader on multiple projects, mentored interns, lectured on CV, AI security and signal processing.
Position: Machine learning researcher (speech technologees)
Category: Data Science
Experience: 11 years | English: fluent

Karaulov, I., Tkanov, D. (2019) Attention Model for Articulatory Features Detection. Proc. Interspeech 2019

Sokhatskyi, V., Zvyeryeva, O., Karaulov, I., Tkanov, D. (2019) Embedding-based system for the Text part of CALL v3 shared task. Proc. SLaTE
2019: 8th ISCA Workshop on Speech and Language Technology in Education
Experienced machine learning researcher focused on speech recognition, synthesis and related tasks. I have 12+ years of experience with speech-related technologies, 19+ years of overall experience in software development. Participated in a number of successful ML projects, as well as in scientific research. An author of papers presented at international conferences such as Interspeech. I have experience not just in research, but also in the integration of AI and ML solutions into commercial projects.

Working Experience

* Voiceitt
Speech recognition for people with speech impairments and highly unintelligible speech. Position: senior speech recognition researcher.
- Creating models and algorithms for continuous dysarthric speech recognition (English)
- Spoken commands recognition for people with speech disorders (language-independent)
- Speech recognition optimization and integration into the server-side solutions and mobile applications.
- Voice conversion and speech synthesis, noise robust ASR and other speech-related tasks

* SciForce
Various AI/ML projects, mainly speech-related.
Position: AI lead, senior ML engineer.
- Recognition and assessment of accented speech for 60+ languages.
- A number of NLP projects dealing with text classification, machine translation, etc.
- Computer vision projects
- Building predictive models for entertainment business

* EnvionSoftware
- Educational software development

* Radmir company
- Software development for ultrasound scanners

Education:
Master of Applied Math,
Kharkiv National University of Radioelectronics, Department of Applied Math
I have 12+ years of experience in machine learning (20 years of commercial experience in software engineering). My main interest lies in audio/speech technologies, as well as natural language processing. I've successfully created competitive speech recognition systems dealing with non-standard and unintelligible speech. I'm keen on creating new non-standard solutions for solving non-standard problems. Although I prefer research tasks, I have broad experience in creating end-to-end solutions
Position: Machine Learning | Ruby | Python
Category: Ruby
Experience: 3 years | English: fluent


ruby python rails machine learning aws docker
no front
Position: Machine Learning Scientist, Quantative Financial Markets Analist
Category: C++
Experience: 5 years | English: intermediate

Strong programming skills include Algorithms Design and Analisys, OOP, Design Patterns, C++, STL.

Machine Learning technologies as Neural Networks, Probability Graphical Models (BN, DBN, HMM, MN), Statistical Analysis, Time Series Analisys and Prediction, Classification and Clasterisation methods.

Well knowledge of financial math and quantative analysis of financial markets (Risk Analysis, Mean-Variance analysis, Decision Theory and so forth...)
-
- C++, QT, STL, Python, R, Matlab/Octave
- Machine Learning, Statistics & Data Analisys, 
-, Quantative Analisys of Financial Markets
Prefer hard scientific and research tasks, sophisticated math algorithm design, various machine learning and data analysis tasks (regression, pattern recognition, prediction and so forth). Prefer remote job.

Very interested in job related to quantative financial analisys and adjacent areas, in simple words [ML + Quantative Financial Analysis]
Position: machine learning specialist
Category: Data Science
Experience: 4 years | English: fluent


I'm an AI specialist with 4+ years of experience in applying machine learning and data mining methods in analysis of data. As a machine learning engineer and applied machine learning data scientist, I have built and deployed systems in the financial and technology domains. My current researches are broadly in the areas of machine learning, NLP, and applied probability.
Position: Machine Learning Team Lead
Category: Lead
Experience: 3 years | English: fluent

- Developed Multi-Object tracker that took 2nd place in KITTI competition (pedestrians)
- Was responsible for architecture on 3 ML projects
- Developed system of gathering statistical data on bugs coming from clients and their analysis
- Studying for PhD in Computer Science (topic related to Swarm Intelligence and Robotics)
- Completed multiple courses on Machine Learning
- Completed multiple books on DevOps, Teams organization, Management
Samsung Electronics (2 years)
- Machine Learning Engineer (computer vision)
- Development of multi-object tracker
- Team's Scrum master
- Responsible for software architecture and code quality
- Set up and supported continuous integration

Microsoft (1.5 years, still working)
- Software Engineer
- Support and development of product's core functionality
- Team's Scrum master
- Automation of workflow processes
- Participation in workload analysis and distribution
- I would really like to try a Team Lead position for a small emerging team (preferably working in Machine Learning field)
- Ability to start work at least in 1.5 months as I am currently working abroad
- Interested in Reinforcement Learning
- Full-time official workplace
- Product company, not outsource