lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: ML/DL engineer
Category: Data Science
Experience: 2.5 years | English: intermediate


During the first internship, I was involved in the development of a recommender system for a music application. At my next job, I developed face recognition system using RetinaFace and ArcFace. Also developed random forest model for time-series forecasting task (prices of laptops in local chain of stores).
Position: ML/DL Team Lead
Category: Lead
Experience: 11 years | English: upper

As a senior ML/DL engineer - developed many different ML/DL models, including but not limited: auto classifier (predicts brand, model and generation), fridge freezer and microwave classifiers (predicts on/off events), personal traits classifier, clients churn predictor.
As a team lead - created a team (7 developers and 3 data collectors) which successfully developed the following image processing algorithms: porn detection for images and videos, multi categorization of images for advertisement, images search by image, clothes search, logo detector. 
As a CEO of own startup - found ML outsource clients, took care about office and built a small team (3 people) with focus at ML/DL outsource projects, the team successfully completed the following ML/DL projects: faces verification, spoofing detection, object detection/search pipelines and fish detector.
More than 10 years experience as software engineer/senior ML engineer/team lead/CEO of own startup. Worked in many startups (Europe, North America) and mediums size companies; ex-Yandex, ex-Facebook. 
Skills: C++, cuda, python, machine learning, neural networks, algorithms, data structures, team management.
I am looking a job as a team lead/engineering manager of ML/DL team and currently I am NOT interested in any other positions or roles.
Position: ml engineer
Category: Python
Experience: 0 years | English: upper

I am studying at the best IT university in Ukraine Kyiv-Mohyla academy. Completed courses on Kaggle: “Python”, “Intro to machine learning”, "Intermediate machine learning”. I have completed a specialization “Deep learning” on Coursera.
I wrote basic projects for the university program such as a graphics and text editor and a graphics game and simple models for courses I took part in.
Model for predicting prices and model for optimizing placement of goods on shelves(Hack4Retail by McKinsey & Company and Fozzy Group in 2021).
Model for predicting churn segment of drivers(INT20H 2022 Hackathon). Model for the reconstruction of RGB images to hyperspectral ones(CSC2431H UofT course in 2022).
I don't like testing and frontend development
Position: ML engineer
Category: Data Science
Experience: 1.5 years | English: fluent


Analysis of user behavior, construction of machine learning models, analysis of model data in order to improve the performance of already working solutions. Development of convolutional neural networks for recognition of English texts and images. Data visualisation and presentation of model results to the team.
Position: ML engineer
Category: Python
Experience: 3 years | English: pre


Developed and implemented 3D positioning and Tracking algorithms. Implemented computer vision algorithms with OpenCV. 
Built classifier with transfer learning using Keras (for example, based on Densenet) and XGBoost model for image classification in scikit-learn. 
Collected, studied and interpreted large datasets using CVAT (annotator for video), Jupyter, Matplotlib.
Developed services saving videos and params of the videos in the database (PostgreSQL). These services were packed into docker-containers.
Position: ML engineer
Category: Data Science
Experience: 0 years | English: fluent

1. Diploma with honours (bachelor's program in Applied Mathematics at Kyiv-Mohyla Academy). I also completed a certificate program "Mathematical Foundations of Machine Learning".
2. I was accepted to multiple prestigious American and Europian univeristies for Master's studies in Computer Sceince. Although I was unable to take those programs since I was unable to leave Ukraine, I still consider this an achievement. Most notably, I was accepted to Carnegie Mellon University and Brown University (Ivy League).
3. Olympiads.
  a) Gold Honour in International Youth Math Challenge
  b) 20th place in All-Ukrainian ICPC
4. Conferences. I participated in 3 scientific conferences: XXI International Scientific – Practical Conference «Shevchenkivska Vesna – 2023», International Conference of Young Mathematicians, and XI All-Ukrainian Scientific Conference. In all cases I gave talks in graph theory.
5. I passed a TOEFL test (result: 118/120). This proves that my English is on Advanced level.
Everything is evidenced by certificates or other means.
First, I participated in a research project conducted by students from Kyiv-Mohyla Academy and University of Toronto "Continual Learning in Medical Imaging". Within the project I researched different techniques of continual learning and applied them to the specific problem in order to estimate their efficiency. 
Second, I passed Deep Learning and Tensorflow specializations on Coursera learning platform.
Third, I successfully worked on an internship "Advanced C++ and low-level software development".
I see my development in the sphere of Artificial intelligence, more specifically machine learning. To this end I took a Master's program in Computer Science at Kyiv-Mohyla Academy.
My preferences concerning my future occupation are the following: I want my job to require creativity rather than purely technical abilities, and I want to apply deep learning in my work. At present though my foremost goal is to obtain experience, after which I may tweak my wishes.
Position: ML engineer
Category: Python
Experience: 0 years | English: intermediate

I had passed second course faculty of Mexanics and Mathematics. I had been receiving a regular scholarship and increased stipend for 1.5 years and 0,5 year respectively.
I had had 3 week practice in Samsung Electronics from intellectual systems, which include next topics: classical machine learning, deep learning and time-series forecasting. Aslo I have experience with different Python libraries such as Numpy, Pandas, Scikit-Learn, Matplotlib etc. And I can use Git(GitHub), if it is need.
Position: ML engineer
Category: Data Science
Experience: 2 years | English: upper


I have extensive work experience as an AI Engineer with a fast-paced startup team. In this role, I designed and developed several natural language processing projects including named entity recognition and sentiment analysis. I also created predictive models and was responsible for some MLOps activities. Additionally, I have some experience with front-end development.

Prior to my work as an AI Engineer, I worked as a Robotics and Programming Teacher. In this role, I developed excellent communication and explanation skills, which helped me to effectively teach complex concepts to students.
Challenging tasks, new experience
Position: ML engineer
Category: Data Science
Experience: 0 years | English: upper

During study practice I had to write a script that converts csv file into pandas data frame, clears the DF and save data in DB. First of all I had to look at data in csv file in order to decide which technique use to create a DF. The DF was created, after that it had to be cleaned. There were a lot of cells with missed values. All rows with missed values had to be deleted except if cell is not in admissible column. There weren’t any "dangerous" NA values, so I could continue. But one column had wrong format of data, so I had to delete rows with wrong format. One column had urls and not all of them were responding. So I had to delete rows with the urls weren’t responding. And finally the DF was clean. Every URL is a way to download file, I had to download all of them, extract HTML content from them and save HMTL in MySQL db. 
I you want to see code I could show it at the meeting or we can have a calling. For writing script I used Python and libraries such as numpy, pandas, requests, bs4, pathlib, os, shutil, aspose-words, re, mysql and json.
I have no commercial experience. I have only experience in my university, include study practice. I also had certificates from DL.ai. During studying in university I had study projects: Paint in PyQt, Library App in PyQt and an experiment to show how regular expressions make life easier for programmers in C/C++.
Position: ML engineer
Category: Data Science
Experience: 0 years | English: upper

Cources:
Machine Learning Engineer 
Mathematics and Statistics for Data Science
Python for data development and analysis.
Links to diplomas are in resume.
QA Engineer 10 years experience. 
Working in banking software, health, gamedev projekts.
2 years of xperience as SCRUM-master.
QA role in development and deployment processes, users technical support.
Position: ML Engineer
Category: Data Science
Experience: 2 years | English: fluent


9 months as Data Scientist / Quantitative researcher at an algorithmic trading company
9 months as Big Data Engineer at outsource project with GCP stack
Current position as ML engineer
Position: ML Engineer
Category: Data Science
Experience: 4 years | English: fluent

- performed end-to-end ML pipeline for vehicle test assistance in automotive
- proven recommendation from Project Manager at Google
- proven as an independent combat unit at complex projects, which I handled for clients myself only
- developed a promotion algorithm which still serves the company faithfully for 3 years already
- AI Engineering for voice processing
- End-to-end ML Engineering in automotive (vehicle test assistance app)
- AWS Ecosystem (Glue, SageMaker, Lambda etc.)
- GCP (BigQuery, GCC, 


Python Stack: Pandas, NumPy, Flask, BeautifulSoup, Scrapy,
Selenium, Matplotlib, Seaborn, SQLAlchemy
ML Stack: Tensorflow, Keras, Scikit-learn, SciPy, XGBoost,
LightGBM
Dashboarding Stack: Tableau, Google Data Studio, Niche
Dashboarding
Databases: Oracle SQL, PostgreSQL, SQLite, BigQuery, MySQL
Notebooks: Jupyter Notebook, Google Colab
DevOps Stack: Docker, Google Cloud Composer, Terraform
Orchestrators Stack: Apache Airflow
AWS: SageMaker, Glue, Lambda, S3, SNS/SQS, ECR, ECS, RDS, EventBridge
Position: ML Engineer
Category: Data Science
Experience: 3 years | English: upper


Computer Vision, Natural language processing
Object detection, classification
Recommendation systems
Photos reconstruction (increasing quality, HDR)
Position: ML Engineer
Category: Data Science
Experience: 0.5 years | English: upper

**Education**
Master and Bachelor degrees in Computer Science (both finished with honors)
IASA, NTUU KPI
(copypasted from CV)
***COMMERCIAL EXPERIENCE***
**GRID DYNAMICS (June 2022 - Present)**
ML Engineer contractor for Apple Inc., majorly handling
full-stack software engineering (Aug 2022 – Feb 2023)
1. Application for drift detection in manufacturing data:
- Backend development | internal platform, Python
- Frontend development | internal UI library, Vue.js
- Data visualization | Tableau
- Statistical algorithms for time-series data development | Pandas, NumPy, Alibi Detect
2. Application for production line optimization:
- Frontend development | Vue.js, Chart.js, Cytoscape.js
3. Other small projects on POC phase:
- Backend development | Flask, Python
- Frontend development | internal UI library, Vue.js

***PERSONAL PROJECTS***
**AUDIO EDITOR WITH ML-BASED INHALE FILTERING**
- Audio files dataset markup
- YOLO features engineering
- YOLO model design and training | TensorFlow, Python
- Desktop app implementation | Jetpack Compose, Kotlin

**STUDY PROJECTS**
- Device classification based on their text description in NLP course | FCNN, LSTM, Transformers
- PageRank algorithm implementation using Spark in BigData cource
- Viola-Jones algorithm training parallelization using CUDA in AI cource

**ALTMOBFOGSIM**
(MASTER THESIS)
- Framework extension development | Kotlin
- Parallel simulations design and execution
- Library source code debugging
- Paper preparation and publishing in academic journal
Position: ML Engineer
Category: Data Science
Experience: 3 years | English: fluent


Developing, testing, and deploying Computer Vision models for a cutting-edge robotic-assisted medical platform focused on in vitro fertilization procedures. The platform integrates state-of-the-art technologies to enable real-time detection, tracking, and morphological classification of spermatozoa and oocytes, along with event detection from microscope camera feeds. 
Responsibilities:
Orchesttrated the complete lifecycle of Computer Vision models targeting diverse objectives (object detection and tracking, instance segmentation, video classification)
Optimized model performance for real-time execution, considering computational efficiency and resource constraints
Fostered dynamic collaboration with other members of the R&D team to ensure seamless integration of newly developed modules into the existing system architecture
Engaged in continuous R&D activities to pioneer innovative solutions in the field
Environment and Tools: C++, QT, Python, PyTorch, OpenCV, ONNX, TensorRT, CUDA
Position: ML Engineer
Category: Data Science
Experience: 2.5 years | English: intermediate

*  In the short time I made a simple MLops solution that was able to prove the value of the project
*  Then made a system for ML development in full, which still successfully performs its tasks
* I constantly showed stress resistance and leadership
Hello, I'm Andrew, an MLOps engineer with two years of experience (2021-2023). Throughout my career, I have been involved in the entire project lifecycle, from initial development to deployment. I have experience developing ML pipelines for video processing and have been involved in web development as well. During a challenging time, I stepped up to take responsibility for another part of the project.

In my role, I have used various technologies, including Python (for ML with PyTorch, NumPy, Pandas, etc.), K8s, Docker, GCP, MongoDB, and SQL. Not only I developed myself as an MLOps engineer, but also as an ML engineer and manager, and leader.  I have also participated in several ML, MLOps, and innovative management courses to continuously improve my skills.

I am now seeking new opportunities in either ML engineering or management positions within the AI industry. I am flexible with compensation(but I need to pay for the flat in Kyiv:)) and eager to learn and take on new challenges. Thank you for considering my application.

Hope to hear from you soon!
non-toxic workflow. 
honesty. 
and have the opportunity to grow, and take the initiative.
You(as a company) don't have any connection with russia and belarus.
Position: ML Engineer
Category: Data Science
Experience: 4 years | English: upper

- Brought Deep Learning into existing ML solution in a ML-oriented product and increased quality metrics for ~10%.
- Developed a custom ML solution for a B2B product, that was the most useful feature for 70% customers.
- Moved 80% projects from PoC stage to production.
- Worked in a full-cycle pipeline of ML product, was involved in stages from data gathering to deployment.
Hi there!

I'm a T-shaped specialist with a major expertise in Deep Learning, passionate about Computer Vision and everything new in Machine Learning in general. 

EXPERIENCE
- Developed a system, that recommends the best photos from the given album of photos. Solution is based on image analysis and includes such approaches like photo aesthetic estimation, object detection, face detection and emotion recognition, image embeddings extraction, clusterization etc. 
- Fully developed a startup Automation of Job Interview Process. Developed all ML algorithms + web part. Integrated NLP - text classification and NER with BERT-based nets, graph similarity, text readability etc.
- Built and deployed product category text generation task on 4 languages: English, French, Italian, Spanish with GPT-2, mt-5 models.
- Developed custom OCR project with math symbols recognition using OpenCV, CRAFT, PSENet etc.
- Developed solution for PII Extraction in unstructured multilingual text using BERT-based nets.
- Developed a project that detects bad photo quality (blur, bad lighting, bad object angles etc.) using OpenCV, ResNet, YOLO etc.
- Developed classic ML solutions like medical data classification.
- Developed Proof of Concepts for such tasks like: Clothes 3D Reconstruction, Clothes Segmentation, Audio and Video Emotion Detection etc.
- Managed 5 developers as a Team Lead.

Also strongly experienced with AWS, Azure, Git, Docker, SQL.
I expect to work with ML/DL tasks with emphasis on Computer Vision. 
Now, I want to grow further in my career and embark on a new adventure, mostly I'd like to work in ML-oriented product. Therefore I'm interested in positions of a ML Engineer with higher level of ownership and responsibility for the product results.
Position: ML Engineer
Category: Data Science
Experience: 3 years | English: fluent


I am a first-year Computer Science and Mathematics student at Columbia University. I am interested in Natural Language Processing, Machine Learning, Data Analysis, and Software development.

I have co-founded and led Pravopysnyk, a project to create AI-powered grammatical error correction for Ukrainian, akin to Grammarly. As part of this project, I built custom NLP models for sequence generation and classification. I also developed the beta version of a real-time text editor web application using AWS, Flask, and Docker. The grammatical correction model we developed achieves a score of 66.3 on the UA-GEC benchmark by Grammarly and outperforms all existing models.

I also have extensive experience in data analysis and mathematical modeling. I competed at Columbia Mathematical Modelling Competition and International Competition in Mathematical Modelling to solve real-world problems. I also worked on data analytics as an intern at both Reply.io and CHCKR.io. Additionally, I have published research in Applied Physics and Mathematics in 11th grade.

I am excited to work on projects that leverage machine learning and data to achieve social impact or create new technologies.
Position: ML Engineer
Category: Python
Experience: 0 years | English: upper


I developed a malaria detection system using neural networks. I mastered TensorFlow Datasets for data prep, applied diverse data
augmentation techniques, and built CNNs using Sequential, functional, and class-based APIs. Callbacks like CSVLogger and
EarlyStopping managed training. I achieved accurate model
training, evaluation, and visualizations like loss graphs and ROC
curves. Demonstrates deep learning proficiency and efficient medical image analysis
Position: ML Engineer
Category: Data Science
Experience: 1 years | English: fluent


I have been working on different kinds of computer vision projects using cnn and other ml models during ACA Bootcamp such as object detection, object segmentation, face detection, digit recognition, car parking app, etc. 
Everywhere I were developing and using my own models of cnn.
Best fit for me is ML in computer vision
Position: ML Engineer
Category: Data Science
Experience: 4 years | English: fluent

Certificates:
Convolution Neural Networks
Structuring Machine Learning Project
Improving Deep Neural Networks: Hyperparameter
tuning, Regularization and Optimization 
Neural Networks and Deep Learning
Machine Learning: Classification
Machine Learning: Regression
IELTS: C1

In addition I have multiple publications in IEEE, Scopus.

Some of them:
Ivan Hahanov, Wajeb Gharibi, Igor Iemelianov and Tamer Bani Amer. QuaSim – Cloud Service for Digital Circuits Simulation. // Proceedings of IEEE East-West Design & Test Symposium.– 2016.– Yerevan, Armenia.– P. 141-158.

Ivan Hahanov, Tamer, Irina Hahanova, Sergey Demen]ev. Automaton MQT-model for Virtual Computer Design. Proc. CADSM, Polyana, Ukraine, 2015. P.27-31.
I'm an ML Engineer with about 4 years of experience. During my practice I've successfully implemented and delivered various projects to international customers all around the world. The domains were diverse including Computer Vision, NLP, 3D models processing and Big Data. I've acted as a main researcher and decision maker responsible of how to approach each problem. Also I've had an experience of leading distributed teams whose members were located in Canada and Russia.
Position: ML Engineer
Category: Python
Experience: 2 years | English: intermediate


In general, I worked in projects, where the task was object detection and object tracking. The specification was that the images were taken from drone, and sometimes there were very small objects that need to be detected and tracked. Also, there was a project about image segmentation and background removal or replacement. 
In my projects I used OpenCv library, PyTorch, work with different neural networks.
Now I am an ML Engenieer and working on a project again about object detection and tracking of objects, that were taken from uavs.
I want to enlarge my work experience and work in projects, that will differ from my current and past projects. Also I want to improve my skills, so I want to get а new job, new apportunities and new space to learn new things and improve my knowledge.
Position: ML Engineer
Category: Data Science
Experience: 2.5 years | English: fluent


I've made a part of a research project in the Computer Science and System Engineering Department (U2IS) in ENSTA Paris. 
My task was to develop deep learning models to directly predict vessel movements from images of the sea surface. In this work, in order to predict ship motion from images, nine deep neural network models were created and tested. Such variety of models is caused by the complexity of the problem. Empirical results show that models with LSTM parts and using additional information such as the current ship motion improve the pitch and roll prediction accuracy. The best result was achieved by a [CNN LSTM encoder-decoder images PR] model. The best combination of parameters was found using the Hyperband algorithm.
Position: ML Engineer
Category: Data Science
Experience: 8 years | English: fluent


ML Engineer and Data Scientist with more than 8 years in the industry

Experience in various technical domains:
	
	- Deep learning
	- Classic ML algorithms
	- Computer vision
	- Signal processing
	- Structured/Unstructured data algorithms
	- Supervised and Un/Self/Semi-supervised ML
	- General Computer Science

and business domains:

	- Medical imaging
	- Augmented reality
	- Automatic speech recognition
	- Speech conversion
	- Fintech
	- AI on mobile devices
	- Marketing

High level results working independently as well as in the team

Good communication skills (fluent English) and mentoring experience (was a Data Science and programming lecturer for years)

Experience in designing and building ML solutions from scratch
Position: ML Engineer
Category: Data Science
Experience: 2.5 years | English: fluent

Maintained full ML production lifecycle for text generation model, including automated data updates, versioning, model storage, deployment, and quality assessment by external team 
Researched and implemented image inference optimisation with quantisation, measuring and documenting performance/accuracy trade-offs, and building a pipeline for training-optimising-deploying on a mobile device (Android)
NLP: managing pipeline for chat dialogue models (data collection and management, training/fine-tuning, deploying, quality assessment); conditional text generation; performance optimisations;
Comp. vision: inference optimisation for edge devices (ONNX runtime, TFLite, quantisation methods)
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