lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Machine Learning
Category: Project Manager
Experience: 0 years | English: upper

I am a graduate of an international UK school, Oxbridge High School
My name is Mohammed Alkhanov, born in the year 2004. I have had the fortunate upbringing of being taught to prioritize an individual's qualifications over their age. As an IT specialist, I possess exceptional skills in time management and team management.

Effective communication and strong interpersonal skills are among my strengths, allowing me to collaborate efficiently within a team. Additionally, I am adept at taking initiative when necessary. Punctuality and motivation are inherent qualities that drive me to excel in a fast-paced environment, consistently delivering work of high standards.

Being an excellent team player, I am receptive to instructions from individuals at all levels and consistently foster positive working relationships with my colleagues. My flexibility, reliability, and remarkable time-keeping abilities further contribute to my professional capabilities.
Position: Machine Learning
Category: Data Science
Experience: 1 years | English: fluent

B.S. of Computer Science and minor program in Economics at KAIST - one of the best universities in the world (according to QS ranking - 33d position in Computer Science, 46th position in general).

- Dean's List award for high scholastic achievements and outstanding leadership.
- Work experience in international startup company (Korea).
- Number of projects related to Machine Learning.
- Research experience.
- Coursera online certificates.
- Additional projects: TCP/IP stack implementation, basic OS development (PintOS project).
Programming Languages: C, C++, Python, Java, Matlab, Bash, Assembly.
Libraries and frameworks: TensorFlow, Keras, NumPy, OpenCV, Flask, Asyncio.
Tools: GDB, GCC, git, Microsoft Visual Studio, Intellij IDEA, Eclipse, Docker.

Experience in Machine Learning (Computer Vision), Networks, Low-level programming, IoT.
Have a strong knowledge in algorithms/math/statistics.
Proficient user/administrator of Linux systems (Ubuntu).
I'm a dedicated and motivated senior student seeking a challenging full-time Software Engineer position that will allow to take full advantage of the passion and knowledge, as well as will provide opportunities for further development of my skills.

Job in data science/machine learning/deep learning/AI/NLP-related projects is highly preferable. 
However, I am also interested in Networks or IoT-related fields. 

Opportunities for scientific researches would be a great plus.

Not interested in: web development.
Position: Machine learning AI Engineer
Category: Python
Experience: 2 years | English: upper


Graduated from Taras Shevchenko National University of Kyiv,  speciality Computer Engineering, Master's honours degree. Currently studying for a postgraduate degree at Kyiv National University, majoring in Computer Engineering. 
During last 3 years worked in area of AI/NLP (Convolutional Neural Networks) in university research, have 4 publications in this area. I also worked with time sequence analysis and image analysis, clustering.
Previously worked as a programmer/analyst at Start Us Insights (remotely) and at EVE.calls.
I would like to work in the area of AI/Machine Learning.
Position: Machine Learning and Data Science Engineer
Category: Data Science
Experience: 7 years | English: intermediate


Software Engineer with strong mathematical skills and 7+ years of
experience in computer vision, deep learning, software developing,
multimedia processing, optical character recognition, and digital signal analysis.
Has excellent knowledge of modern computer vision and deep learning approaches.
Highly motivated and passionate Engineer whose goal is to solve real-world problems.
Position: Machine Learning Architect
Category: Lead
Experience: 8 years | English: fluent

- I created Data Science function from zero in 700+ people IT company, engineered its structure, developed ML strategy, acquired A-class talents of all kind (Python Developers, Data Scientists, Data Engineers, ML Engineers, DevOps, BA) and ensured growth of 4 new disciplines (NLP, CV, ML based forecasting, VR). It continues to grow and deliver after 3 years I left my post. 

- Recorded four electronic-music albums. 

- Managed to get myself to MIT.
HEAD OF DATA SCIENCE — Jul 2018 - Oct 2020

- Accomplished creation and leading of R&D department, created and implemented road map for the development of Data Science function in the company by introducing Data Science Strategy, by opening new specialisations like Natural Language Processing, Computer Vision, Time Series Analysis and by acquiring talents meeting growing needs and changing conditions. I nurtured team of 20+ people.

-Developed product portfolio for propelling digital transformation and automation for marketing, e-commerce, supply chain and logistics with $ 4M+ cumulative impact on the bottom line. The projects included NLP for Marketing Automation, CV for food recognition, ML for forecasting, procurement and fulfilment optimisation as well as development of decision making tools based on AI.

-Ensured evolution of technical road-map for establishing effective data-science products delivery routine. Established standards and policies for data science process without damaging experimentation culture.  

CO-FOUNDER AND PRINCIPAL DATA SCIENTIST — Nov 2017 - May 2018

- Co-Founded company specialised on algorithmic cryptocurrency trading. 
- Developed model-driven architecture based on Microsoft Stack (Azure Cloud Services, MS SQL, Microsoft R, PowerBI) for model deployment and BI and node js for trading automatisation. 
- Achieved average classification accuracy for predicting market trends up to 55%.  


DATA SCIENCE PRODUCT MANAGER — Jul 2015 - Dec 2017

- Developed SQL+R based MVP for clustering customer preferences inside product groups, which led to increase in sales by 1,5% and EBIDTA Margin by  0.4%.

- Defined a new data driven inventory management process. The effort resulted in 4~6% reduction of inventory holding costs (approx. 8M $ in investments in stock).

- Managed implementation of TMS. Achieved successful integration with WMS and ERP systems and unlocked potential for yearly economy of $ 3M+.
I will make best fit to:

1) A company in desperate need of creating its own Data Science function from scratch. 
2) An organisation with ongoing process of Data Science practices implementation.  

Preferably mature international business with established processes, rapid bureaucracy cycles and strong IT.
Position: Machine learning / Computer vision engineer
Category: Data Science
Experience: 3 years | English: fluent


Ph.D. student in Computer Vision at the University of Lille (France), CRIstAL lab. Working on real-time and mobile models for visual perception tasks.

Previously worked as a machine learning engineer in the field of language processing, including, but not limited to, tasks such as text classification, named entity recognition, metric learning for textual data, audio classification, and adversarial speech detection.

Aside from the main job, I also did an internship at the University of Toronto, where I've been working on a video classification model that will be deployed on a mobile device, suitable for lower-limb exoskeleton control. And I hold a Kaggle Competition expert title, with 3 competition silver medals.
Position: Machine Learning (Computer Vision) Engineer
Category: Data Science
Experience: 0 years | English: intermediate

Have experience of several high-intensity practicums with mentors from Samsung R&D Institute Ukraine (during my B.S.).

Successfully worked with modern networks, such as:
- YOLO
- MobileNet
- Inception
- R-CNN (Fast/Mask)
- ViT/DETR
- SegNet

Also have experience of working with GAN-s.
I would divide it into 3 sections: Applied Mathematics, Computer Science, and AI. 

R, Matlab, SageMath for applied mathematics, Python and C++ for computer science, and scikit, xgboost, tensorflow, pytorch, and opencv for AI. This list, indicative of my primary toolkit, is far from exhaustive but is tailored to meet the evolving demands of today's tech landscape.

If we'd talk about projects: there are a variety of applications. Classical machine learning algorithms, neural networks, computer vision problems, computer statistics (R), soft computations, applied mathematics (dynamical systems, mathematical physics, mathematical methods in cryptography).
I would like to work on some challenging, advanced project which requires advanced knowledge in applied mathematics as well as in computer science and AI (ML/Dl/CV/soft computing).

Shortly, my B.S. title is literally "Computer Mathematics".
Position: Machine Learning / Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: upper

- Optimized data gathering process, which sped up annotation time and reduced cost of annotation
- Optimized inference pipeline for huge amount of data.
- Took responsibility for communication with business representative for better connectivity between ML team and business.
Last 2 years I've been working with image data as an ML/CV Engineer. This includes
- Research and hypothesis definition
- Data Engineering: retail data, satellite data, video
- Model Training: object detection, instance segmentation, metric learning
- Model Deployment: creating API, porting into edge devices.
- Model Monitoring and Maintenance: automation pipelines and error analysis
Position: Machine Learning / Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: fluent

Hackathons winner and participant, constant self-learning.
Main projects:
Computer vision R&D development and research. Image processing. 3D Computer Vision tasks. Object detection, tracking,  reconstruction.
Social networks analysis, natural language processing projects (news analysis, profiles analysis, person character estimation).
Tabular data science: SQL, Pandas, PySpark, anomaly detection, forecast.

Key responsibilities:
R&D computer vision:
Metric development, model selection, data processing, training, transfer-learning, demonstration of work. 

Social networks project:
Data collection, unstructured data processing, queries, estimations, natural language processing analysis of posts, and comments of a person for creating an overall person profile, clustering by person embeddings, friends, groups and interests.
Interested in computer vision, image-video processing, multimodal deep learning, algorithms/model development and deployment.
Position: Machine Learning | Computer Vision Engineer
Category: Data Science
Experience: 3 years | English: fluent


As a computer vision and machine learning engineer with more than 3 years of experience, I had the opportunity to work on several exciting projects that involved developing innovative solutions for different industries.

The first project was focused on real-time obstacle detection and road sign classification for a self-driving car system. My responsibilities included designing and implementing the machine learning algorithms that would enable the system to detect obstacles and road signs in real-time. This involved working with large datasets of images and video footage to develop and train the machine learning models. The project was a success, and the solution was able to detect obstacles and road signs in real-time with a high degree of accuracy.

The other project involved the development of a full-scale vehicle identification and analytics tool. The tool had modules for vehicle detection and tracking, body type, make model, and color classification, as well as license plate recognition. My role on this project was to design and implement the computer vision algorithms that would enable the system to accurately identify and classify vehicles based on their make, model, body type, and color in real time from multiple sources. I worked with large datasets of vehicle images and used diverse range of machine learning algorithms and tools like TensorFlow, PyTorch, OpenCV, sklearn, pandas, numpy and etc. to develop and train the models. I also worked on the integration of the algorithms into the system's software architecture, ensuring that the models could run efficiently and accurately process large volumes of data. Custom data flow pipeline was developed that enabled the system work with multiple sources seamlessly in real time and be fault tolerant in case of failures. The project was a success, and the tool was able to accurately identify and classify vehicles in real-time, providing valuable insights and analytics for transportation management and planning.

In addition to my work on industrial projects, I also had the opportunity to participate in research projects, including one focused on topology optimization using GANs. My research focuses on exploring the application GAN models, to optimize the speed and efficiency of topology optimization solvers. The goal of this work is to enhance the performance of these solvers, with the aim of making them more practical for industrial use and improving overall optimization results.
Position: (Machine Learning|Computer Vision) Engineer, Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper

Developed and deployed document verification service with quality comparable to SOTA paid APIs.
Designed solution for clothes transfer.
Fozzy group R&D Temabit
Computer Vision Engineer
Worked on Smart Cart project. Analyzed competitors' solutions to learn their mistakes and advantages.
Researched and tested the newest deep metric algorithms for retail product classification with a huge number of classes and only a few examples per class.
Tested different mechanisms of barcode recognition for hard cases. Prepared datasets for data segmentation with a semi-supervised method.

eCommerce startup Mod-y
Data scientist & Co-Founder
Designed solution for clothes transfer from one photo to another. Analyzed business needs to define the appropriate strategy for end-to-end algorithm development. Implemented demo for potential investors.
Researched and adopted different 3d open-source solutions: smpl human restoration, pix2surf, clothes generation. Worked with Blender API for 3d rendering. Deployed and trained advanced generative neural networks for clothes transfer: pix2pix hd, vitonhd.
Developed and deployed auxiliary tools. Trained and evaluated neural networks for clothes segmentation, human parsing using PSPNet, U2net, M-RCNN architectures. Deployed and adopted open-source pose detection.
Trained, improved and deployed cutting-edge superresolution model SR-3 to upscale photos from 256x256 to 1024x1024.
Developed algorithm for accurate background change using auxiliary tools (background matting, openpose) to geometrically properly put humans from one scene to another.
Analуzed different ways to deploy service backend on AWS. Deployed services using EC2 instances, S3 buckets and Lambda functions.
Researched and implemented optimization techniques to speed up service inference and reduce costs: quantization and OpenVino runtime to significantly speed up models on CPU.

Fintech product company
Junior Machine Learning Engineer
Maintained, developed and improved facesearch service. Developed and deployed 3d face alignment detection and 2d face aligner. Designed and deployed mechanism for detection of percent of the closed face on customers photos. Collected statistics to understand the influence of different data corruptions and noise on face search algorithm.
Trained and tested CNNs(plenty of SOTA classifiers) for documents. Trained and evaluated model(PSPNet) for document segmentation. Used Bayes CNN to filter inappropriate data. Developed mechanism to align documents on photos and make them scan-like...
Can't describe more due to characters limit
I'd like to work on interesting and challenging tasks that will give me opportunity to  improve my proficiency. I want to become part of  a high-skilled team to learn from them and I'm opened to share my experience. I'm searching for vacancies on Computer Vision, NLP or robotics. Mostly I have experience in Computer Vision but I'm open for little bit lower offers in NLP.
Position: Machine Learning/Computer Vision Engineer/MLOps
Category: Data Science
Experience: 4 years | English: fluent

Got to work on a tool aimed for use in malaria drug development, which should help microbiologists create a cure for the deadliest disease in the human history.
Machine Learning Engineer (May 2020 - Present)

Designed and implemented a pipeline for visual analysis and grouping of malaria drugs for mosquitoes based on the shape changes in the infected cell after drug administration. The pipeline produced results similar to that of manual inspection by the microbiologist, while taking orders of magnitude less time to analyze the data. [DVC, YOLOv5, PyTorch, Dash, Clustering, Dimensionality Reduction, Object Detection]

Machine Learning Engineer (Jan 2020 - May 2020)

Developed a scalable image classification service for items on the smart scales with F1 score of 92% to minimize amount of physical interaction between the store customer and smart scales. [Tensorflow, Image Classification, Google Vision AutoML, Kubernetes, FastAPI]

Designed and implemented a template pipeline for object detection projects to speed up the development in the future, which was reused on 3 separate projects and resulted in 60h+ of engineering time reduction per project. [DVC, YOLOv5, Object Detection]

Implemented a POC for retail fraud prevention system for use in stores with self-checkout to prevent self-scan fraud.[DVC, sklearn, Classification]

Implemented a distributed version of association rule mining algorithm to analyse up to tens of billions of records about customer purchases.[Apache Beam, DataFlow, BigData]

Machine Learning Engineer (Jan 2020 - May 2020)

Implemented an easily reusable, resumable and reproducible pipeline for language model training to speed up and simplify LM training for text generation in Ukrainian.[GPT-2, DVC, Natural Language Processing, Text Generation]

Machine Learning Engineer (Mar 2019 - Dec 2019)

Designed, developed from scratch and deployed a reverse image search engine for movie and event poster recognition, data matching and search to be used in a social network app.[Apache Airflow, PyTorch, Kubernetes, FastAPI, Scrapy, Reverse Image Search, AWS]

Android Developer (Aug 2017 - May 2019)
I am looking for a MLE position, preferably related to Computer Vision and also interested in MLOps tasks (pipeline management, experiment infrastructure etc.).
Position: Machine Learning/ Computer Vision specialist
Category: Data Science
Experience: 4 years | English: upper


Person detection/tracking. Facial classification such as age, race, gender with custom nets for low res images. Attributes like glasses. 
Video action detection: public street fighting, fall detection.
Scenes with smoking detection on films for age restriction. Titles detection for movies/series.
Amazon pods detection and classification whether it’s shelfs is closed or not.
Parse relevant text information from photo of ID cards/ license cards/ Bank checks.
Curse words real time detection on speech. 
Neural network compilation/pruning/quantization for faster inference using TensorRT. 
Gpu programming on CUDA, ILGPU.
Creating and improving sport predicting models.
Position: Machine Learning / Data Engineer
Category: Data Science
Experience: 4 years | English: fluent


- Coding using Java, Python, Groovy
- Designing and implementing ETL processes for data pipelines using Glue, PySpark, Spring Batch
- Building predictive models using machine learning techniques (XGBoost, Random Forest)
- Design and development of web services / microservices for ETL steps (Spring, Falcon) and ML models (scikit-learn, PyTorch) and its CI/CD integration (Docker, Kubernetes, AWS, CircleCI, Git)
- Anomaly detection using SparkML
- Designing and developing various data mining applications for natural language processing: web crawlers (HtmlUnit/HttpClient) and search systems (Lucene)
- Database knowledge: SQL (MySQL, Aurora, Postgres) and NoSQL (OrientDB, MongoDB)
Position: Machine Learning/Data Engineer Python
Category: Python
Experience: 11 years | English: fluent

Creation of Machine Learning based services that helped to automate a lot of human work and made company more profitable and competitive.
Creating of data warehouse that made data access fast and easy, and helped to make a lot of valuable data insights.
Creation of  high performance hybrid PPC/RTB advertising platform with effective analytics components.  Building data pipeline.
Creation of FISOAP: traffic tracking/scoring system.
Creation of useful platform components that lead to an increase in KPI.
Effective cost lowering by refactoring hardware and system design (e.g 70+ to 10+ servers)
7 years of experience in web applications design and development.		
6 years of experience in Machine Learning (NLP), Data Science/Engineering/Analytics domains		
3 years of experience as Project Lead in digital advertising building PPC/RTB arbitrage and data-oriented applications/components.		
1 year as Security Officer in digital advertising company in malware/fraud protection		
1 year as Head of Technical Support in digital advertising company		
1 year of experience in financial/business analytics		
		
- Passionate about The Data, able to work within deadlines, self-motivated, team player, self-studied person. Have desire to accept new challenges.		
- Ready to investigate and find solutions for issues with different levels of complexity.		
- My hobbies: self-education, reading books, playing guitar, yoga and everything that can help being happy and healthy.
Interested in:
Working in a data-driven company, developing data-centric products, 
in Machine Learning, Data Engineering teams,
building data pipelines, AI-based services, training models. 
Python/Go/JS stack;
Possible relocation: EU