lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Computer Vision Android/C++ Developer
Category: C++
Experience: 1.5 years | English: upper


Architected and developed from scratch using various computer vision algorithms a Makeup AR-tist application and released it to android play market:
- have a significant experience deploying CNNs on Android OS, worked with various inference frameworks
- created a library using openGL for optimized drawing makeup elements (draw masks foundation, eyelash, eyeliner, highlighter etc.)
- implemented and optimized filter2D, gaussianBlur, treshold etc shaders to get the smooth and stabilize picture of the makeup elements
- integrated an internal face trace SDK into the application
the face trace SDK itself was optimized to utilize Android GPU: cartToPolar, warpAffine, pyramidDown

During the work with inference framework I actively use PyTorch for next 
purpose:
- tuning model
- create test code for pretrained model 
- converted model for different inferences
Eager to learn new technologies while developing products.
Prefer product companies with a small team
Position: Computer Vision and Video Streaming Lead/Architect
Category: Lead
Experience: 11 years | English: fluent


I have got more than 10 years of experience being in the software development industry. This includes working for both large companies and small startups.

My primary specialization is video streaming. I built large platforms and small solutions for all kinds of web streaming: broadcasts with RTMP based technologies and real-time communication services with WebRTC. This experience includes both architecture design and hands-on development.

Besides video streaming, I have an expertise in ML learning engineering with computer vision bias.
Looking for senior positions at small companies or emerging startups.
Position: Computer Vision C/C++, Python
Category: C++
Experience: 0.5 years | English: fluent

Projects:
- Smart Environment for a Mobile Robot Tracking a Robot through a camera, processing a real-time videostream using OpenCV and navigating the robot through remote ROS node, running a ROS master on Raspberry Pi 3b+
- Eimeria Bacteria Dataset classification using Deep Learning Automatic detection and classification of Eimeria species using CNN YOLOv3
-FPGA Implementation of Stochastic Computing Primitives for Vision Applications

Publications:
- ROS-based Integration of Smart Space and a Mobile Robot as the Internet of Robotic Things
- Towards the Internet of Robotic Things: Analysis, Architecture, Components and Challenges
2021 April - now
Maddevs - Junior Computer Engineer

Jun2019 - Sep2019 
RESEARCH INTERN in SOFTWARE ENGINEERING LAB - INNOPOLIS UNIVERSITY, RUSSIA
Researching for Internet of Robotic Things, developing a project that integrates IoT devices and robot

summer of 2017-2018
COMPUTER ENGINEERING INTERN (C language ) - YILDIZ TECHNICAL UNIVERSITY
Position: Computer Vision / C++ / CUDA Developer
Category: C++
Experience: 3 years | English: upper


R&D Graphics Engineer, ZibraAI; Kyiv, Ukraine
November 2022 - Present
 Developed and maintained the Unreal Engine version of Zibra Effects.
 Designed and implemented new RHI interface, leading to improved plugin performance and
compatibility.
 Optimized shaders and resources for enhanced graphics rendering.

Middle C++ Computer Vision Developer, Tsukat; Lviv, Ukraine
May 2021 - November 2022
 Created advanced 3D tracking solutions using single-camera and multi-camera setups.
 Developed real-time light and reflection model, improving realism in computer vision applications.
 Accelerated computation on WebGL backend, resulting in faster and more efficient processing.

Research Assistant, Infineon Semiconductor; Lviv, Ukraine
August 2020 - May 2021
 Applied Reinforcement Learning and Graph Neural Networks to optimize Bluetooth Low Energy
mesh networks.
 Collaborated with a multidisciplinary team to enhance network performance and reliability.

Software Developer (C++/CUDA), DeepTrait; Lviv, Ukraine
February 2020 - June 2020
 Parallelized main algorithm using a cluster of GPUs, reducing computational time from 9 hours to
2.5 minutes.
 Designed a compression algorithm that lowered memory consumption by 3x, improving application
efficiency.
Position: Computer Vision / Data Scientist
Category: Data Science
Experience: 2 years | English: upper

I consider myself a passionate and disciplined individual, thus these traits always bring success to me. I got accepted to the world-class Charles University with a special scholarship.
As a computer vision engineer, I have a strong background in researching, designing, and implementing innovative algorithms for a variety of projects, including license plate recognition, vehicle make-model detection, and face recognition. My expertise in Python programming and PyTorch deep learning framework has been crucial in developing scalable, robust, and accurate computer vision systems for large-scale datasets.

I have also utilized Nvidia DeepStream technology and RabbitMQ for efficient communication and handling of a vast number of streams in my projects. In my current role, I collaborate closely with stakeholders, researchers, and engineers to drive systems from prototyping to production level, effectively bringing my ideas to fruition in real-world applications.
In my next role, I am looking for a dynamic and collaborative work environment where I can use my skills and experience to make a meaningful contribution to the company's success. I am looking for a position that offers a competitive salary, as well as benefits such as health insurance, vacation time, and opportunities for professional development.

I am open to a variety of responsibilities and am eager to take on new challenges. In particular, I am interested in working on projects that involve the application of my computer vision and machine learning skills, and I am excited to work with a team of talented and passionate professionals.

I am flexible and open to negotiation on certain points, but I believe that a fair and competitive salary is important for the long-term success of both the company and myself. I am confident that with the right mix of responsibilities and support, I will be able to thrive in this role and make a valuable contribution to the team.
Position: Computer vision / Deep learning engineer
Category: Python
Experience: 7 years | English: intermediate

Passed the way from the first deep learning frameworks (FANN, Caffe). Developed several custom deep learning algorithms for image processing (more detailed in communication).
6 years of experience in Image processing algorithms development.
Deep learning implementation for image processing.
Languages: python (main), C++ (secondary).
Technologies:  tensorflow, pytorch, numpy, openCV, scikit-learn, scikit-image, pandas, scipy, gdal.
Working with image processing / deep learning algorithms. Research, proof of concepts, challenging tasks, team work, new experience.
Position: Computer Vision/Deep learning Engineer
Category: Data Science
Experience: 4 years | English: fluent


May 2022/Aug. 2022
Company: Pic-time
Description: Deep learning engineer
Responsibilities: Developing and maintaining neural network based computer vision system for face detection and unsupervised human re-identification
Technologies: Python, Pytorch, Docker

Jul. 2020/Aug. 2021 
Company: Lynx
Description: Game Developer/Mathematician
Responsibilities: Developing game engine based on APL-like language Q. Game
engine was simulating ecosystem as dynamical system based on Lotka–Volterra
equations
Technologies: Python, Numpy, Unity, Q-lang

Jul. 2019/Dec. 2019
Company: Samsung
Description: Computer Vision Engineer
Responsibilities: Distance estimation algorithms research, porting code from
Python to C++
Technologies: Python, C++, Tensorflow, libBoost, Docker

Feb. 2018/Feb. 2019
Company: EOS Data Analytics
Description: Data Scientist
Responsibilities: Field edge detection with gabor filter, unsupervised fields de-
tection, segmentation neural networks architecture research for landcover and crop classification
Technologies: Python, Tensorflow, Keras, Gdal, Docker

Aug. 2017/Feb. 2018
Company: Anryze
Description: Data Scientist
Responsibilities: Neural networks architecture research for speech recognition
Technologies: Python, Pandas, Keras, PyWavelets, Python-speech-features
Nov. 2016/May. 2017 
Company: DataRoot
Description: Junior Data Scientist
Responsibilities: Building emotional recognition system and user activity analysis
Technologies: Python, Pandas, Scikit-learn, Keras, Numpy, Pyspark,
Matplotlib, Seaborn, Xgboost, PyMongo

Dec. 2015/Feb. 2016
Company: MedTechCollective
Description: Data scientist intern
Responsibilities: Building food recognition system, data parsing, dataset preprocessing
Technologies: Python, Keras, Caffe, BeautifulSoup, Selenium
Position: Computer Vision/Deep Learning engineer.
Category: Data Science
Experience: 2.5 years | English: fluent

My researches were published in Dr. Vernadsky’s science journal "Scientist's notes" and was published in Tavrian National University's journal. I graduated from School42, Unit Factory, Kyiv.
At UNIT Factory (School 42, Kyiv) I have completed a lot of projects in С(99), that explored graphics programming, game engine development, advanced algorithms, and graphs

I have a couple of commercial projects in the Computer Vision sphere: object detection/segmentation tasks, object classification, object detection, and tracking/detection with classical approaches. I have spent a lot of time carrying the optimizations of DNN's for fast inference using the TensorRT library. I have experience in embedded development using C/C++ and the platform Arduino Nano. I had a deal with streaming technologies such as Gstreamer with NVidia accelerators and I created a few GStreamer plugins based on AI for accelerated video streaming.
 
My last position was a Technical Lead and I lead a small team of developers. Our main goal was to create a cloud-based solution for the AI project. The solution should have been scalable, flexible, and user-friendly. I used a Google Cloud Platform, FastAPI, MongoDB, Apache Kafka, Tensorflow, and a lot of 
accompanying technologies(jinja, poetry, e.t.c).

I would love to carry on using C++ and Python to work on AI projects. My ultimate goal is to develop Computer Vision.
I would be delighted to become a part of a team that is passionate about AI/ML. I believe that a friendly atmosphere and willingness to share knowledge are of utmost importance. 

I am confident that I do not want to work in web development and make it a part of my main stack, but I'm interested in web-oriented AI technologies.
Position: Computer Vision (Deep Learning) Engineer
Category: Other
Experience: 2 years | English: upper


- Face recognition/verification.
- Image classification.
- Image segmentation.
- 3D face reconstruction (3D morphable models and deep neural analogs) for head rotation.
- Custom datasets preparation by deep-learning driven approaches: emotions, pose variability.
- Video based data collection/preparation.

Model Architectures: EfficientNet, ArcFace, SphereFace, FaceShifter, CycleGAN, MobileNet, VGG, ResNet, ResNext, Inception, Xception, DenseNet, SENet, U-Net etc;

Have experience of working in startup and R&D environment. 
Kaggle competitions expert.
Willing to work in an R&D team on challenging tasks, surrounded by passionate people.
Position: Computer Vision / Deep Learning / Machine Learning Engineer
Category: Data Science
Experience: 7 years | English: upper

Updated company’s mmdetection [GitHub] fork from 1.x to 2.x version
- Introduced unified training docker environment (current users approximately 10 people from different teams)
- Improved internal object detection project robustness with unit tests
- Improved internal project object detection model metrics (up to 10% AP for some classes)
- Made models conversion from FP32 to INT8 without decrease of performance and with 5x speed-up using OpenVino
- Created solution using VAE and CatBoost for anomaly detection on thermal power plant
that increased possible crash prediction on the plant (made full research cycle from communication with business to production solution)
- Made full cycle of research for Customer verification using computer vision (classification, object
detection with Pytorch), prepared POC versions of models in docker environment
- Created a semi-automated system for data labeling speed up (clouds detection + pre-segmentation)
- Created several dockerized versions of models a) for vehicles detection outside of the cities
b) for city buildings type segmentation
- Created robust deep learning models using UNet for agricultural fields borders prediction
- Leaded process company participation in the challenge Facebook Geo Workshop for CVPR 2018 ( - Participated on behalf of Company on Kaggle Airbus ships detection challenge - that helped company’s marketing
- Created salary cap model for globalfantasysports platform for basketball, golf, and American
football
- Created ML models for fantasy points prediction, an algorithmic model for automated team selection, ML models for match outcome prediction and performance of each player in the upcoming game
- Prepared full documentation with Python code examples for backend team on how and what data to use from data providers
- Introduced and maintained Knowledge Base about ML and analytics side of the project in Attlassian Confluence
- Made full research of competitors (e.g. Fanduel and DraftKings)
10 years of experience in different domains (Computer Vision, Data Science, Machine Learning, Deep Learning, Analytics, Business Intelligence)
Advanced knowledge of deep learning for computer vision tasks, machine learning methods (clustering, regressions, decision trees), statistics.
Machine Learning competitions - Kaggle Master, Top places on other platforms (TopCoder, Codalab, CrowdAI)
My main objective is to solve business problems and needs using Machine Learning / Deep Learning/ Computer Vision technologies, continue to grow as a data science and machine learning expert, continuously improve my programming skills. Extraordinary interesting tasks – this is what I am looking for.
Position: Computer Vision & Deep Learning Researcher / Research Engineer
Category: Data Science
Experience: 4 years | English: fluent


Programming Languages: Python • C/C++ • MatLab • Java.
Technical skills: Pytorch • Tensorflow • Caffe • OpenCV • Git • Android Studio.

Languages: Fluent in English, Russian and Ukrainian; intermediate working proficiency in Korean.
Position: Computer Vision developer
Category: C++
Experience: 11 years | English: intermediate

Have experience in Computer Vision (stereo vision, obstacle avoidance, surface estimation) using OpenCV & CUDA on Windows and Linux, performance optimization.
Have 10+ years experience in hydrological numerical modelling.
Strong mathematical skills and algorithmical mind.
- C/C++, Fortran, Pascal, VBA, Batch/Bash scripting
- Parallel computing (CUDA, OpenMP, MPI) for Windows and Linux
- OpenCV, ROS
- MATLAB, AutoCAD, ArcGIS, Aquaveo SMS, DHI MIKE Software
- MS Visual Studio, Eclipse IDE, Borland Delphi IDE, Git/SVN
- Strong mathematical skills
Looking for a Computer Vision/Applied Math job.
Have fun doing good and interesting projects.
Position: Computer vision engineer
Category: C++
Experience: 2.5 years | English: intermediate


Fullstack developer (ASP.NET MVC + KnockoutJS), support and feature integration.
Computer vision engineer (Python, OpenCV, C++), system development for traffic analysis.

I want to find company where I can grow as specialist and work on interesting projects.
Position: Computer vision engineer
Category: Data Science
Experience: 1 years | English: upper


Hey, my name is Yurii, I`m from Lviv, Ukraine. I was working in Embedded for a year, but I was always interested in ML and especially in computer vision. Now I have up to a year of experience in ML and computer vision. I reproduced the best approach from the Yelp restaurant classification on Kaggle, as my course project for the AI course in Ukrainian Catholic University. 
Now I am working on a Startup, where we are trying to develop a system to classify different formations on Mammography scans.
I expect to have an interesting project where I can learn something new and work with a team of professionals.
Position: Computer vision engineer
Category: Data Science
Experience: 2 years | English: upper


Machine learning engineer with 1.8 years of experience. Confident computer vision engineer, but eager to constantly discover new areas of expertise. Motivated and a very fast learner. Excellent team player with experience in mentorship.
Position: Computer vision engineer
Category: Data Science
Experience: 4 years | English: upper


My main field of expertise is Computer Vision and Python. I worked with projects which used face recognition, object detection, object tracking, image segmentation, image processing and optical character recognition.
Position: Computer Vision engineer
Category: Data Science
Experience: 10 years | English: fluent

Developed detection and tracking solutions for people, cars, obstacles, traffic signs, etc. AI solution optimization.
Skills:
- PhD. in mathematics, statistics, probability theory, mathematical modelling. 
- Computer vision, Machine learning (AI, neural networks).
- Requirement management: from elicitation to validation. 
- Product management: from training data gathering and labelling to prototyping and high accuracy solution development.
- SDLC: Project management (waterfall, scrum), project management documentation development.
- Team management.
Product company only (no out-sourcing or out-staffing)
Position: Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: upper

Proficiency in Python
Good skills in heuristics Computer Vision methods: OpenCV, trimesh
Understanding of Machine Learning architectures
Math degree
2 years as Machine Learning / Computer Vision Engineer in Data Science company
- Worked with 3D
- Several projects in sports
- Unsupervised learning experiments
1 year as Python Engineer in Data Science and Data Engineering company
Looking for Computer Vision positions only
Position: Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: fluent


About
Main areas of interest:
- Medtech
- AR/VR Applications
- Image processing
- Real-time Deep Learning inference

Tech stack:
- C++(for ML/CV backend), Python(for fast prototyping)
- OpenCV, OpenGL ES, Metal, Google's Mediapipe, Intel's OpenVINO
- IOS deployment, AVFoundation, Swift
- Build systems: Bazel, cmake
- PyTorch, Tensorflow 2.0, Keras
- Linux/MacOS, bash, protobuf/json, Docker

I'm an accomplished Machine Learning Engineer with a proven track record of success in high-pressure, real-time environments. My expertise lies in cutting-edge computer vision technologies, particularly in the areas of Medtech, AR/VR, and computer graphics. Whether it's developing real-time deep learning models or deploying complex systems at scale, I'm always up for a challenge. If you're looking for a dynamic and versatile team player with a passion for innovation, look no further. I'm ready to hit the ground running and take your organization to the next level.
Position: Computer Vision Engineer
Category: Data Science
Experience: 1 years | English: upper


Academic/freelance/personal projects

1)Computer Vision Engineer at CaaI - tennis game analysis; real-time Video Analysis, Tensorflow, Keras, openCV, Nvidia Jetson,TensorRT (full-time job) - dec. 2020 - current time

2)MEG (magnetoencephalography); signal analysis  features extraction, data analysis, Python, pandas, numpy, scikit  (freelance) - oct. 2019 - mar. 2020

3)Object detection(safety vests at the airport scene, thumbnails on websites); Tensorflow, Keras (pet, freelance)

4)Hough Transform for detecting 3D spheres on the MRI images; Python, OpenCV, Multithreading   (freelance)  - apr. 2019

5)Signal processing of accelerometer data from the running sensor; Python, Bluetooth (pet) 

6)Liver pathology detection (ultrasound images); OpenCV, Python, Qt (academic) 

7)Desktop applications; Python, QT (academic, freelance)
Computer Vision is the most interesting topic where I want to improve my skills and get solid expertise.
Position: Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: intermediate

I finished face recognition project and set it in production. Like to visit conferences, meetups, and workshops.
Applying ml algorithms, text analysis (classification), image analysis (image processing, classification, object detection, clustering).  Integration of Natural Language Processing, Computer Vision services into chat-bot.
Researching solution for the biomedical engineering company. Classical Computer Vision + Deep Learning solution for microscopy images segmentation.
Applying modern Machine Learning / Computer Vision algorithms to web applications, security system (face identification/authorization, using deep learning techniques and classical machine learning ). 
Interesting in Computer Vision.
I search product/outsourcing company or startup. I'm fast learning and able to new opportunities. Most interesting field for me - Computer Vision.
Position: Computer Vision Engineer
Category: Data Science
Experience: 0.5 years | English: upper


As a passionate aficionado of machine learning, I have amassed a wealth of experience through various personal and command projects. These projects span a wide range of fascinating areas, including OCR, Keypoints, PnP, Segmentation, Classification, Regression, Detection, NLP, and Data Visualization.

My professional work as a Computer Vision Engineer has been marked by excellence and dedication over the course of a year. In particular, I worked on a structural drawings specifications detection project, utilizing advanced techniques such as image preprocessing, OCR, NER, and object detection.

My academic background includes a degree from the esteemed Karazin National University, where I studied Mathematics and Computer Science.
Position: Computer Vision Engineer
Category: Data Science
Experience: 6 years | English: fluent


Building and leading an AI team including computer vision engineers and MLOPs. 
Engineering own deep convolutional models for object detection, classification and tracking, as well as adapting SOTA pre-trained models via transfer learning technics. 
Implementing self-supervised learning methods for recognition and classification tasks.
Position: Computer Vision Engineer
Category: Python
Experience: 5 years | English: fluent


Computer Vision Engineer - Creative Advanced Technologies(Dec 2022 - Present)
- Creating solutions for both cloud and mobile platforms
- Variety of fields to work in and improve
- Converting machine learning models to use them in edge devices
- Technologies: Python, AWS, OpenCV, FastAPI, Mediapipe, JavaScript, Py-
torch, Tensorflow

Machine Learning Engineer - Hubx(Oct 2021 - Dec 2022)
- Created cool deep-learning models for our mobile solutions
- Deployed our algorithms to cloud platforms
- Worked as a team lead
- Developed the AI side of the three applications from scratch: Mimic - AI Face Animator, AI Photo Enhancer - Photoapp, DaVinci - AI Avatar Art
- Technologies: Python, C++, GCP, OpenCV, FastAPI, PyTorch, CuPY(CUDA
Math for Python)

Computer Vision Engineer - Rapsodo(Jun 2019 - Oct 2021)
- Worked in the team that develops sports applications and solutions
- Focused on ball tracking and pose estimation
- Calculated the best possible pitching guidance using both computer vision
and physics
- Developed frameworks using Swift
- Technologies: Swift, Python, C++, OpenCV

Part Time Software Engineer - Rapsodo(Aug 2018 - Jun 2019)
- Migrating vision algorithms to mobile applications
- Developed tracking and detection algorithms
- Technologies: Python, C++, Swift