lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Computer Vision Engineer
Category: Data Science
Experience: 4 years | English: fluent


Researcher with the experience in development. Actively participated in all stages of production of Computer Vision/Deep Learning models: from data collection up until support in production in various startups.
I expect my next work environment to be a technically skilled team with mainly research vector of development.
Position: Computer Vision Engineer, AI Engineer, Data scientist
Category: Data Science
Experience: 1.5 years | English: upper

Prizes at machine learning and computer vision hackathons
Intern in the development of neural networks  University of Artificial Intelligence
February 2021 г. - February 2022 г.
Was one of the developers of neural network modules
demo.neural-university.ru


2nd place in the finals of the hackathon "Digital Breakthrough 2021"
December 2021
Created a model for the recognition and detection of leaks from oil pipelines


3rd place in the team in the hackathon  Leaders of Digital Transformation 2021
October 2021 - November 2021
The task of detecting paths in an urban environment.
Created a segmentation model


17th in the individual competition  "Digital Breakthrough Championship"
July 2021 - August 2021
Task: Recognition of aircraft on satellite images.
Used data processing, image augmentation, binary classification of images.


PHP Developer
January 2005 - July 2021
Mostly remote work for different companies creating web projects
Interesting tasks that require artificial intelligence
Position: Computer Vision Engineer / AI or ML Engineer / Data Science
Category: Data Science
Experience: 1 years | English: pre


Experience working on real projects (6 month): 
I worked with solutions that take of GPU processing using CUDA. I have experience with image processing using OpenCV, PyTorch, TensorFlow. For example SLAM, recognition of store logos in a mall using YOLO, image deblurring, text to speech ("talking head").
Position: Computer Vision Engineer, Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Earlier winner of few Republican Olympiads in Ukraine in Physics and Math and Master of Science in Physics.
Now motivated computer vision enthusiast.
I'm computer vision engineer so I'm able to process image & video data with segmentation, object detection & tracking, pose estimation and so on with further analysis. As well I'm working with deep learning models and their tuning & training, so want to develop myself in DL/ML/CV fields.
I'm interested in data science field so I'm inspired to participate in Computer Vision or DL projects, but throughout my way in DS I am very motivated and open for different topics.
Position: Computer vision engineer, Data Scientist/ML Engineer
Category: Data Science
Experience: 3 years | English: upper

Successful graduation from the Ukrainian Catholic University with an average score of 4.5/5
I am an alumnus of Computer Science at Ukrainian Catholic University with a specialization in Data Science. I was primarily involved in projects in the field of Computer Vision and statistics.
I have a solid background in 3D Machine Learning and Engineering, cherish being involved in both research and business.
Position: Computer Vision Engineer | Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: intermediate

Kaggle bengaliai-cv19 (Top 6% bronze winner)
Computer Vision Engineer
- Investigate and train deep learning models to develop computer vision algorithms for Manufacturing Industry (Object detection, Anomaly detection, Segmentation)
- Built a pipeline and trained license plate recognition system. Achieved accuracy of 99.2% (С++, Python, TensorRT) for Jetson
- Developed synthetic data generation algorithm for license plates based on GANs. The generated data improved the accuracy of the license plate recognition system by 2% by dealing with imbalanced data
- Researched quantization techniques for deep learning model compression. Managed to quantize the FaceNet model to work on Google Coral
- Working with stable diffusion models(lora, dreambooth) for img2img translating
- Developing vehicle/person re-identification from multiple camera for smart city analytics
- Developed a system that analyzed HTTP requests with regular expressions to prevent malicious behavior. Prevented 95% of the most common HTTP attacks
- Redesigned the app’s architecture from monolith codebase to microservices using Golang, ClickHouse, Postgresql, gRPC. It improved uptime, performance, and scalability
- Designed and developed a Face Recognition system using Angular 6, Django, MXNET, and Postgresql.
I am interested in Computer Vision, and NLP field projects.
Position: Computer Vision Engineer / Machine Learning / Python Developer
Category: Data Science
Experience: 3 years | English: upper

I can work on projects with the following skills:
Python, OpenCV, TensorFlow, Keras, Matplolib, Pandas, PyTorch, NumPy, Git, Scikit-learn, Artificial Intelligence, Artificial Neural Network, Convolutional Neural Networks.
Company name - Construction Estimation Software (startup)
Position - Computer Vision / Machine Learning Engineer, Python developer
Type of employment - full time
Working time - 15.06.2020 - 14.12.2021 (1.5 year)
My tasks were programming the computer vision algorithm, preparing the dataset for model training.
---
Company name - AIFY (startup)
Position - AI Engineer, Python developer
Type of employment - full time
Working time - 20.12.2021 - 04.06.2023 (1.5 year)
My tasks were training models for classification, writing algorithms for object detection and many more projects
Position: Computer Vision Engineer / ML Engineer
Category: Data Science
Experience: 2.5 years | English: upper

- completed several courses for Computer Vision, Machine Learning, and SQL competence
- English (IELTS - overall 7.5 С1)
- created stable solutions for CV tasks that showed stable performance in different environments
- suggested a process optimization inside team workflow that was successfully implemented and used on a daily basis
- conducted risk assessments of credit portfolios with over 100 000 entities
- automated a significant portion of the evaluation process
I am an experienced Computer Vision Engineer with a track record of creating safety-checking modules using object detection, pose estimation, segmentation, and classification approaches. I am proficient in both classical CV techniques and Deep Learning for object tracking and segmentation and have worked extensively with remote servers to set up environments for training and inferencing deep learning models. I have a strong interest in research and continuously strive to improve the performance of my modules, implementing the latest approaches into production-ready products. Additionally, I have experience in leading a small team of developers, integrating processes for testing models, and ensuring proper data storage. My key toolset includes PyTorch, YOLO, OpenCV, MMPose, norfair, numpy, git, and dvc.

Previously, I worked as a Junior Data Analyst, where I wrote advanced SQL queries to extract data from data warehouses, conducted risk assessments of portfolios, evaluated potential returns with statistical analysis, and automated the data preparation process and exploration analysis for new portfolios using Python (pandas, numpy, matplotlib). I have experience building operational analytical reports using Excel and visualizing results in PowerPoint. My key toolset for this role includes SQL, pandas, numpy, matplotlib, and other data manipulation libraries.
I am preferably looking for a challenging project in the Computer Vision area (interested in discovering and applying not only Deep Learning approaches but also classical ones). 

Also, I would gladly discuss opportunities for Machine Learning projects in varying domains.
Position: Computer Vision Engineer | Tech Lead | Head of CV / ML / AI
Category: Data Science
Experience: 11 years | English: fluent

More than ten years of extensive software development experience, Computer Vision, ML/DL and Data Science. Proficient with 3D, 2D approaches, deep learning, statistics, video streaming. Completed several projects for mobile platforms, developed algorithms for high-load solutions, self-driving cars, IoT, robotics, 5G. Few years of leadership experience. Participated in tens of pre-sale calls with top management, roadshows, many business trips to EU and USA, customer on-site activities. Managed a project with up to ten third-party suppliers, supervised and mentored junior engineers, conducted plenty of interviews for junior/middle/senior positions. Developed a large bulk of solution for image enhancement for Samsung camera default application. Optimized its processing time from 5 minutes to 50ms by integration of more efficient algorithms and substitution of the third-party solutions by the development of own modules. · Developed an algorithm for objects localization for further recognition and classification, which has 4 times higher precision than the previous solution with the smallest loss in performance and recall, has approximately the largest recall between the world research institutions (summer 2015 status), and one of the highest f-score. Algorithm also has better recall and precision than competitors´ products on the world market.
Computer Vision Python Image Processing Deep Learning Machine Learning Self-driving cars Autonomous Devices IoT Edge computing Mobile computing Satellite Imagery Aerial Imagery Video Processing Python C++ 360 cameras Augmented Reality Amazon Web Services
Development of sophisticated algorithms in Computer Vision and Machine Learning/Deep Learning scope with social impact (preferably for a startup). Shares would be a great plus. And I am not ready to relocate.
Position: Computer Vision Engineer, TL
Category: Data Science
Experience: 10 years | English: upper

While working as a computer vision team manager developed two MVPs in very short time.
One more computer vision product from idea to appstore and googleplay.
Worked on Samsung Gallery app, won Samsung topcoder.
International conferences participation.
Looking for:
Algorithms, Computer Vision, Machine Learning, Team Lead/Engineer position.

While working as a computer vision team manager delivered two MVPs in very short time. One more computer vision product from idea to appstore and googleplay.
Worked on Samsung Gallery app, won Samsung topcoder.
Research.


Team management - 3 years.
Computer Vision, Machine Learning - 5 years.
Algorithms, Data structures - 12 years. 
C\C++ - 5 years.
OOP, Design Patterns - 4 years.
Functional Programming - 5 years.
CAD, 3D, OpenGL - 1.5 years
Computational Geometry - 1 year.
STL - 4 years. 
Android, Java - 1 year.
ObjectiveC - 1 year.
SQL - 1year.
Worksection,Git,Perforce,SVN,Jira,TeamCity.
English proficiency – upper-intermediate level.
Preferably product.
Inventions.
Business trips.
Position: Computer vision/machine learning consultant
Category: Data Science
Experience: 7 years | English: fluent


Work in computer vision since 2012. 
CTO of the startup with deep-learning based tech.
Multiple papers on top CV/ML conferences.
I can help with design of the machine learning pipelines, data gathering process, hypothesis generation, technical solutions, MVP.

Not interested in production development or full-time position.


P.S. The "salary" is a rate per hour.
Position: Computer Vision/ Machine learning engineer
Category: Data Science
Experience: 1.5 years | English: upper


The main responsibility is to optimize the neural networks (NN) that solve the computer vision problems with minimal size for further deployment in mobile apps. For the TouchRetouch app, I with colleague developed NN for mesh removal tool, which include segmentation and classification meshes on the image.  I also did R&D for upcoming  apps, the methods include skin segmentation, style transfer and super resolution.
Position: Computer Vision/Machine learning Engineer
Category: Data Science
Experience: 5 years | English: upper

The industry-recognized and award-winning CV features of our product make me happy to have had an impact on it and IMO, are my greatest accomplishment as a CV engineer and later a CV lead.
Some of my recent achievements:
- improved our service's performance by 20% while also saving 15% in costs.
- introduced few-shot learning for one of the product features and made adding new classes much faster (1-2 weeks -> 15 minutes) and independent from DS team load
I'm a machine learning engineer with 5 years of experience. For most of my career I worked on computer vision problems and at the moment I'm in charge of the whole computer vision direction at my present employer. I`m a product-oriented person, that prefers improving user experience and business metrics rather than doing stand-alone machine learning research. I worked with object detection, image classification, metric learning, text detection and recognition, image search, and a lot of other computer vision tasks.
I have a high sense of ownership and follow the principle of “Getting Thighs Done” to ship research to end-user in the best and the fastest way, so I have experience with Docker, Kubernetes and Github actions to be able to own everything from beginning to end.
I also have experience with traditional machine learning and natural language processing, such as topic modeling, text classification, web page element extraction and classification, bot detection, churn prediction, etc.
Things important to me:
- ability to have an impact on the product
- challenging business-oriented tasks
- result-oriented environment.
Position: Computer Vision / Machine Learning Engineer
Category: Data Science
Experience: 2 years | English: intermediate

I implemented a defect detection system. I successfully applied the algorithms to my tasks and deployed them in the cloud. I finished "Data Science School" from UCU.
I have experience to apply machine learning algorithms. I mainly worked with images: preprocessing, classification and object detection.
I implemented an algorithm for detecting defects in an image using classic machine learning. I have experience deploying a ready-made model for the cloud (AWS) for the task of computer vision. Have experience in the OCR problem (Optical character recognition). I have experience in development as a Python developer. 
I am a student of Computer Science and have gone through the "Data Science School" from UCU.
Interested in Computer Vision
I search startup or product/outsourcing company. I am fast learning and want to find a good and experienced team.
Position: Computer Vision / Machine Learning Engineer
Category: Data Science
Experience: 3 years | English: upper


Python, Java
Cassandra, MongoDB 
Scikit-learn, Pandas, NumPy, SciPy, OpenCV, Tensorflow, Keras, ROS, NetworkX, Flask
Docker
Computer Vision, Natural Language Processing, Machine Learning, Deep Learning, 
Neural Networks, Time series, Pattern recognition, Optimization, AI
Interesting projects. Ability to continuously develop myself.
Position: Computer Vision/Machine Learning Engineer
Category: Data Science
Experience: 5 years | English: fluent

I have developed a real-time visual tracking system for autonomous servilance and security applications.
I have developed novel 2d/3d perception algorithm based on Deep learning for an automotive industry.
I have helped a company in implementing and integrating Camera based intelligent surveillance module into their existing Embedded system.
I have over five years of experience in software development in multiple companies.
As a holder of a Joint Master's degree in Computer Science Engineering with a specialization in Image Processing and Computer Vision, I have worked in multiple Industries as well as in Research and Development facilities in the area of Machine Learning, Computer Vision, and Artificial Intelligence.
Position: Computer vision & Machine learning  Python developer
Category: Python
Experience: 3 years | English: intermediate


SKILLS
Python3: OpenCV, Pandas, Numpy, Tensorflow, PyTorch, Keras, Scikit-learn, Scikit-image, Matplotlib, Tesseract
Matlab: Neural networks, Signal processing, Image processing, Video    processing
WORK EXPERIENCE
Python developer (CV & ML) 
JUN 2019 – TODAY
The goal of the main project was to detect gems and extract their properties (gem type, color, shape and size). Photos received from the mobile application were processed on the server, and the processing result was returned to the mobile application.
Several projects were related to audio processing: measuring the BPM and key of an audio file and then updating the tags. But the hardest audio project was getting chords from audio recordings.
Artificial Intelligence specialist
JAN 2019 – JUN 2019
The main goal of the project was to detect the bottle, then select the label on the bottle, then compare this label with the customer's base of labels and recognize what the label is in front of you. There were daily morning meetings with an English-speaking customer.
Freelance CV & ML Engineer
JAN 2012 – TODAY 
Various projects, mainly related to computer vision.
I was involved in the "Internet of things" project. We make modules for smart home and security from accessible parts that anyone can replicate at home himself or order modules from us
The last project of mine involved a smart pill dispenser for a US customer. I developed face recognition for patients, checking the number of pills dispensed by the image, monitoring the mechanical parts of the dispenser by video.
I definitely don't want to do web development.
Position: Computer Vision / Machine Learning Research Engineer
Category: Data Science
Experience: 5 years | English: upper

1. Created custom ultrafast object detectors
2. Build a lot of prototypes of computer vision pipelines
3. Speeded up neural networks without losing accuracy
I am a data scientist who mostly specializes in computer vision and deep learning.

I have 2+ years of experience of building computer vision products:
mostly for retail and usually using neural networks.
And 3+ years of experience of machine learning development.

My responsibilities are full cycle of ML development: 
1. Collection and cleaning of image/video data
2. Organizing annotation of image data
3. Choosing and training models
4. Preparing models for production (inference optimization) 
5. Inserting models into the existing pipelines
6. Full pipeline accuracy evaluation
Position: Computer Vision / Machine Learning Trainee
Category: Python
Experience: 0.5 years | English: upper

I managed to get the Bachelor’s and Master’s diplomas with honors in Optical Engineering and defined the area of my interests for future carrier.
The main achievement in soft skills area is gaining confidence in my brain and ability to learn everything.
SPS Commerce – Software Engineer (4 years)		         	         Trading partner development in an e-commerce company. My role includes creating configuration service for data exchange and transformation, as well as analyzing business requirements for customer’s dataflow. During my employment I have improved my skills in technologies, connected with data transformations as well as soft skills such as self-organization, communication with foreign colleagues and building work process according to Scrum methodology.

The main goal now is to get experience and develop my skills in algorithms, machine learning, computer vision and artificial intelligence since I consider these areas as the most exiting and useful for society.
My key priority is constant learning and developing skills. I don't like doing stupid work and can't ignore lack of deep understanding of any process.
Position: Computer vision Project manager
Category: Project Manager
Experience: 10 years | English: upper

live in Germany
Personal profile
I am reliable and well organized.
I have more than 10 years of experience in IT field as a Project Manager cooperating with big Enterprise organizations.

Key skills
Strong practical knowledge of IT projects planning and implementation process with HW and SW integration based on corresponding project team player's skills and customer needs.
Focusing on customer needs and goals of the project. Ability to manage the team to achieve project goals.  

Company-oriented, fast reaction to customer needs. 

Watchful for details, ready to do extra work and able to cope under pressure, responsible, flexible, active, stress-stable, initiative.

Pyinmsgesearch Guru (Computer vision) certificate.

Communication languages: English (Fluent); German (A1); Ukrainian & Russian (Native);  

Interests: 
Business process management and development technologies,
ERP, CRM, MRP, PLM solutions to combine with hybrid HW architectures.
Computer vision, Robotics, IoT.
I am interested in projects of Computer Vision,  IoT, AI, ML domains.
Position: Computer Vision / R&D engineer
Category: Data Science
Experience: 2.5 years | English: upper

I have finished great amount of courses on Coursera, among which is Deep Learning specialization (5 courses) from deeplearning.ai.
I have research experience during two internships (short-time) at Samsung R&D Institute. First topic was "Game bot detection using Machine Learning approach". During this research I investigated and learned how to use such algorithms (classifiers) as Logistic Regression, Decision Tree, Ensembles of classifiers (Random Forest), K-Nearest Neighbours (K-NN) algorithm. Also, I learned about core notions of machine learning, such as supervised learning, precision and recall, bias and variance, overfitting, boosting etc.
We have gone through full development cicle: from creating game bot and collecting data to providing analysis for the results of our models.
Second internship marked the beginning of writing the course work paper, which topic was "Sign Language Recognition using Deep Learning". In this work I presented visual-based system for Sign Language Recognition. My approach uses convolutional neural networks (CNN) to analyze spatial features and recurrent neural networks (RNN) with LSTM cells to analyze temporal features of the video data. Model was trained and evaluated on Argentinean Sign Language dataset and achieved accuracy up to 90% for small part of the dataset (10 signs) and accuracy up to 83% for the whole dataset (64 signs).
I would like to work on the deep learning projects, especially Computer Vision tasks. But other Machine Learning applications are acceptable too. I am interested and ready to perform such tasks as data exploration, creating and evaluating different models, improving the accuracy of existing models. Also i am interested in data gathering and would like to upgrade my skills in this area. It is great if the work requires to read and analyze latest Machine Learning papers.