lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: ML Engineer
Category: Data Science
Experience: 6 years | English: fluent


Over the past 8 years, I have been involved in several research and development projects requiring NLP solutions. From 2015 to 2017, I worked as a research assistant at the ISP RAS Institute (I created a Russian part-of-speech tagger and contributed it to the NLTK library). In 2017, after completing my Software Engineering bachelor's degree. I worked as the lead of a newly established NLP laboratory by ISP RAS. At the laboratory, our work focused on problems of text classification, morphological, syntactic and semantic analysis, using word embeddings (e.g. fastText), language models (such as BERT, GPT) and their task-specific fine-tuning. These results have been published in international computer science journals and conferences.
One significant achievement of our team was the development of software tools for plagiarism detection in Armenian texts. These later became the foundation of my PhD thesis, which I defended in 2021 , and the resulting software system is now deployed in several higher education organizations in Armenia. Since 2022, we extended this research to also assess other aspects of text quality (structure, semantic coherence,etc.) apart from originality, and the results are currently used in RANEPA academy. The implementation of these projects required a wide range of NLP and ML technologies (from rule-based methods and smaller statistical approaches to LLMs, model fine-tuning, quantization, etc.).
In the meantime, I also supervised relatively smaller projects such as the collaboration with the INALCO institute’s DALiH project to collect from the web and classify Armenian
texts in various dialects; the addition of NER support for Armenian language to Stanford’s stanza library; collaboration with the National Library of Armenia to OCR their catalog of books and articles, etc. All of these projects helped gain specific knowledge and expertise in various text processing areas, including also data collection and preprocessing, annotation guidelines development, annotation automation and quality verification.
As the team supervisor, I mentored and facilitated the professional growth of
newcomers, overseeing the recruitment and development of the team from 5 members in 2018 to 15 members in 2023. Guiding the professional growth of my colleagues has been one of the most rewarding aspects of my work.
Position: ML Engineer
Category: Data Science
Experience: 1 years | English: upper

I am a  highly motivated Junior Machine Learning Engineer with 1-year of experience as a Speech Data Processor and a strong passion for technologies. I consider myself a quick learner and ready to work hard.
Looking for an interesting position in a nice team, while upgrading my skills. Ready to start as a Trainee and prove myself to get a permanent position.
Salary can be discussed.
Speech Data Processor in an AI startup - 1 year 1 month
- Data Processing (preparing data to train, feature extraction, and so on)
- Training and debugging ML models
- Designing and conducting ML experiments
- Onboarding newcomers in my team
Experience with:
Python, Bash, Linux, PyTorch, TensorFlow, various ML libraries for python, AWS, Azure, Docker, Git.

I have a strong passion for technologies and want to grow as ML/DL Engineer or Data Scientist. I'd like to work on AI technologies and solutions.
Ready to start with Junior/Trainee position.
No gambling, bookmakers, and microloans, please.
Position: ML Engineer/Android developer
Category: Python
Experience: 3 years | English: upper

Researched and implemented Text To 3D Scene pipeline
Implemented JPEG-like GAN which compresses images better than JPEG
Compressed JPEG-like GAN model to perform on mobile phone (pruning, quantization, spacing, distillation)
• Researched JPEG and H.264/H.265 image/video workflows
• Implemented JPEG-like visual features for GAN image compression
• Compressed model to work on Android devices
• Created several pages of the Android app using Jetpack Compose

• Research and implement Text To 3D Scene pipelines
• Research Geometric Deep learning models to extract 3D objects features
• Feature engineering

• Researched and implemented Human Pose Estimation (2,5d) pipelines
• Feature engineering

• Build RL NN with PyTorch.
• Write some DS projects for the "codefinity.com" educational site.

• Data preprocessing and analysis with scikit-learn and XGBoost,
• Writing SQL queries
Position: ML Engineer / Data Engineer
Category: Data Science
Experience: 3 years | English: fluent

- Optimization of big data data flow to decrease costs up to 400 times (1TB to )
- Development of models is capable of turning cash flows up and costs down. 
- Creation of models with a higher level of metrics than previous solutions, required by business
- Automating handwork to cost optimize processes in business, saving thousands dollars per week. 
- Leading developers to accomplish tasks and documenting business processes to bring light of business vision to development team for right direction.
- 400+ solved leetcode problems
- 150+ solved strata problems
Experienced Software Engineer with 3 years of Machine Learning and Data Engineer, specialised in Retail, Banking, Telecom, Creative fields. And have experience as Data engineer with rolling big data for pipeline (ETL, ELT). 

As a machine learning engineer, I have experience in developing end-to-end machine learning solutions. I am familiar with the entire machine learning pipeline, from data collection and preparation to model training and deployment.

My team was realising scoring models, business reports, monitoring churn models. A data-driven data scientist with highly adaptive skills in analysis and investigation. Have a strong problem-solving skills, critical skills and the ability to accomplish complicated tasks.  Easily can speak with international clients to complete End-to-End Machine learning projects.
I expect experienced CTO, responsible and mature colleagues, who can take ticket tasks and accomplish them. I respect team, who is thinking of one's turn to read their code (do not forget about documentation). The team is able to delegate tasks and strive for knowledge.

Deployment and designing of models for highly data intensive workloads (end-to-end). Working with AWS, maintaining Big Data.
Position: ML Engineer, Data Engineer
Category: Data Science
Experience: 2 years | English: fluent

Successfully leaded the research, Deep Learning models training and models deployment in the Neural Machine Translation area using OpenNMT-py framework.
Python3, OOP, PEP8
iPython, Google Collaboratory, VS Code, PyCharm
Machine Learning (Scikit-Learn, Pandas, Numpy) 
Data Visualization (Matplotlib, Plotly, Seaborn)
Deep Learning (TensorFlow, Keras)
Basics of MLOps (TFX)
Basics of Airflow
SQL (subqueries, stored procedures, window functions) 
Basics of Docker, Kubernetes, Minikube 
Basics of GCP, AWS
Professional Data/ML team, career planning, established processes, professional working environment.
Position: ML Engineer/Data Engineer/MLOps
Category: Data Engineer
Experience: 6 years | English: upper

Numerous ML related projects. Bringing ML models to production. Expertise in Video Processing, Edge Devices, MLOps, Realtime recommendations systems.
Started with different small Data Science project. Evolved into building IoT systems based on Computer Vision algos. Implemented MLOps for such systems. Then switched to cloud based ML systems with strong focus on MLOps side.
Product company with ML-centric product.
Position: ML engineer/Data Science
Category: Data Science
Experience: 0 years | English: fluent

Created several trading strategies based on Momentum and Statarb. 

Masters thesis S&P and VIX Option Pricing with Long Memory: FIGARCH(1, d, 1) and LSTM vs Neural Network
Worked mostly in FinTech related to portfolio construction and entry signals using Deep NN and particularly LSTM.
I have an academic background in Finance and ML/DL and I'm seeking the continuation of this track in the industry.
Position: ML Engineer / Data Science
Category: Data Science
Experience: 6 years | English: fluent


Data Scientist at Microsoft (vendor)
Nov 2018 - Present · 3 yrs 5 mos
• Led the development of the NLP System to analyze clients' demands and behavior, availability of products through different stores, and salespeople performance
• Led the development of an algorithm to identify Microsoft / Azure / Skype accounts that are associated with criminal activities that violate terms of use
• Led a project in finding relationship between a group of phishing kits by clustering them by developing Machine Learning pipeline based on Unsupervised Deep Learning algorithm
• Decreased time spent on manual daily processes by 80% (from 50mins to 10mins) by fully automating Machine Learning (running classifiers, false-positive analysis and etc.) and data off-boarding processes using Python
• Decreased the number of false-positives of Image and Text classifiers by 80% and time spent on false-positive analysis by 50% by developing a new filter for false-positives based on Python script
• Mentored junior data scientists
• Designed, developed and delivered Multilingual Text classification pipeline (for 9 languages) based on NLP algorithms from scratch (with 97% of F1 Score) 
• Increased numbers of identified Tech Support Frauds by developing new Multilingual Text classifier (a 7x increase)
• Decreased time spent on manual daily processes by 58% (from 2hrs to 50mins) by automating Machine Learning (running classifiers, false-positive analysis and etc.) and data off-boarding processes using Python
• Played a key role in preventing criminal activities that violate terms of use by detecting data, analyzing it and sending reports to special teams
Position: ML Engineer / Data Science / Computer Vision
Category: Data Science
Experience: 2 years | English: upper


Experienced in developing and deploying advanced machine learning models. Skilled in data preprocessing, feature engineering, and model training. Collaborative team player delivering robust ML solutions. Up-to-date with latest advancements.
Position: ML engineer, Data Scientist
Category: Data Science
Experience: 5 years | English: intermediate


I started out as a nuclear physicist who know how to code. I have experience with computer vision.  Project work:
*Developed MVP Integration of advertising into a real-time video stream stack (OpenCV, C++, SQL). 
*OCR for mobile application(FastTextScan). 
One year of experience in classical ds and ml. 
*Predictions of customer churn for local mobile operator.
*Time Series
*data visualization and so on.

I have been working with sound for the last 4 years (2 years in Galamat It holding and then almost 2 years in DauysKit startup as senior ML engineer) and have experience with ASR, TTS, KWS, VAD, emotion and gender recognition, biometry.

*We built a speech recognition system from scratch for the Kazakh language.
That solution include:
1. Development of a speech corpus collection platform (cool achievement, we collected 10 000 hours labeled speech data in 4 months, hundreds of active users).
2. Implementation and training SOTA. (helps us to do conclusion and finish experiments before open source implementation).
3. Design and development of microservice architecture.
4. Inference optimization and deploy our speech recognition system on cloud.

With 10,000 hours of Kazakh data, it is easy to transfer the model for other low-resource Turkic languages like Kyrgyz, Tatar, and Uzbek with extra low data. 

* Collect two language speech data from professional actress in order to build bilingual tts.
* Development no-code conversational platform (B2B, B2C) for chat bots.
Position: ML Engineer / Data Scientist
Category: Data Science
Experience: 2 years | English: upper

- Bachelor degree in Applied Mathematics. Faculty of Applied Math at NTUU "KPI". 2018-2022
- Top 15% at Kaggle "Shopee - Price Match Guarantee" competition. May 2021
- Completed Coursera "Deep Learning Specialization" and "How to Win a Data Science Competition: Learn from Top Kagglers". 2020
ML Engineer, May 2021 - Current
Neuroshop.tech
- Creating a system for automated grocery products selling in vending machines with help of computer vision and deep learning
- Collecting datasets and training neural networks for object detection and feature extraction tasks
- Working with popular DL models such as YOLO, MobileNet, OSNet
- Optimizing models for inference via TensorRT
- Deploying ML pipeline on NVIDIA Jetson edge devices

Unity GameDev, August 2020 - December 2020
Self-employed
- Developed an Android game in a team of two. The game was released in alternative stores by Playades.
Position: ML Engineer, Data Scientist
Category: Data Science
Experience: 5 years | English: fluent

Successfully defended PhD
Presented my research in international conferences
1) 1 yr - Technical support for WordPress plugins

2) 2yrs - Project manager, Technical support manager in IT company
Responsibilities:
Coordination of development and testing teams
Defining project tasks and prioritization
Preparing technical documentation

3) 4.5yrs - research and PhD in Machine Learning for healthcare application 
- Physiological signal processing and Exploratory data analysis (Python)
- Applied CNN and Xgboost using Python to develop tool for preterm neonates outcome prediction
- Publications in peer-reviewed journals
- Presented on a number of international conferences (USA, South Korea, Ireland and others)

4) 2ysr - Senior ML engineer in industry (LSTM, CNN, Xgboost, Clustering, visualization tools).
On top of technical work, defining specs and requirements for projects via meeting with customers; presenting results during meetings.
Ideally combination of technical work with management
Position: ML Engineer/Data Scientist
Category: Python
Experience: 2 years | English: upper

A neural network that finds problems on a site based on user session records.
Recommendation system based on user activity on the site.
ML Engineer/Data Scientist (2 years):
•Building NN models (PyTorch)
•Building recommendation models
•Reading papers
•Data preprocessing
•Writing SQL queries
•Results validation & visualization
Personal advancement
Interesting tasks
Good team)
Position: ML Engineer / Data Scientist / Algorithm Developer
Category: Data Science
Experience: 2 years | English: intermediate

Successfully built a system to recognize smartphone usage scenarios, which achieved over 95% final accuracy. 

Participation and award winning in various ACM-like programming contests.
.NET, C#, C++, Algorithms, OOP, Design Patterns.

1.5 years experience in R&D, .NET, C#, C++, Machine Learning Systems, Math (Probability theory, Statistics, etc.) and functional programming.

Participation in commercial projects in field of machine learning and data analysis, particularly in user behaviour analysis and prediction. 

I have a solid mathematical background and the ability to learn new technologies and subject areas.
R&D. Challenging and complicated projects, ability to learn and use state-of-the-art algorithms and techniques with focus on major CS. Professional growth. Server side development.
Position: ML Engineer, Data Scientist Engineer NLP
Category: Python
Experience: 2 years | English: intermediate

I have been programming since I was 12 years old. He has extensive experience in web development, non-standard tasks and deep learning
Hello, I am looking for a job as an ML engineer. I finish the Andrew NG Deep Learning specialization course, I know the basic ml algorithms and statistics. Have extensive freelancing experience, I know python and many other programming languages
Complex and interesting projects. Opportunity to learn from professionals, acquire skills and a minimum income to continue development
Position: ML engineer, DL engineer, Computer vision engineer, NLP engineer, Data science.
Category: Python
Experience: 0 years | English: intermediate

A month ago I create a web site where i publishing some of my new projects that can be useful for another people.
I don't have commercial experience. But I make a lot of neural networks for myself. Some of them classified animals another analyze text. One of the last program I made using ML is monitune. Its adjust screen brightness according to what theme is at the moment white or black.
I would be appreciate if my work is connected to deep learning or machine learning sphere. Creating DL or ML model is what I can do and what I like to do the most.
Position: ML Engineering
Category: Data Science
Experience: 3 years | English: upper


Built a recommendation system for banking products that cut down on marketing expenses.  
Developed a credit scoring model to reduce the number of defaulted loans. 
Utilizing supermarket receipts, predicted customer income groups with a high level of accuracy.  
Created visuals for digital banking to show potential bottlenecks and speed up the process.
Position: ML Engineer | MLOps
Category: Data Science
Experience: 7 years | English: upper

2019 - GCP Professional Data Engineer Certificate
2020-2023 - numerous certificates from Cousera and deeplearning on CNN, NLP, ML in production (MLOps), Attention models.
Software Engineer with 7 years of experience. Last 2 years I have been developing my skills in ML discipline, especially in NLP with Transformers (translation, Sentiment Analysis, TextToCode GPT model), Image Recognition. Prior to this, I gained valuable experience as a Lead Test Automation Engineer.
Programming languages: Python, JS/TS, basic Golang, basic Rust.

Throughout my career, I have contributed to building ML systems and web apps, mobile apps, setup CI infrastructure on clouds, verify system performance and quality, AI models accuracy, worked with BigData

My tech skills currently include: 
- building ML solution with sklearn, PyTorch
- training models with Accelerate, Pytorch Lightning
- preprocessing data with PySpark, pandas
- Docker, Kubernetes, ArgoCD
- orchestration with MLflow
- model inference with Nvidia Triton, FastAPI
- testing: great-expectations, chispa, pytest

Beyond my technical skills, I have proven leadership experience and a track record of mentoring engineers. I conducted tech interviews of potential candidates and have experience as a assessment expert. I take an active role in public and community speaking engagements, where I share my knowledge and insights.
Position: ML Engineer / MLOps Enginner
Category: Python
Experience: 5 years | English: upper


More than 5 years of engineering and leadership experience in R&D, Machine Learning and AI. My core believes are threefold: AI should help people, not replace them, Team should be as close to end-user as possible, Engineer should struggle for best practices.
•	Programming: Python (proficient), C++ (basic), Rust (learning)
•	ML, CV, DL frameworks: pytorch, tensorflow, sklearn, pandas, xgboost, opencv
•	Backend: HTTP, RPC, FastAPI, Redis, RabbitMQ, Celery
•	Testing: unittests, pytest, sonarqube
•	CI/CD: Docker, Docker Compose, Kubernetes, Helm, Nexus, Github Actions
•	Cloud and Monitoring: AWS, Graphana stack (Prometeus, Graphana, Loki)
•	Other: Monorepo (pants 2), Power Tools (pre-commit, poetry, pipenv), inference servers (nvidia triton)

Currently looking into more MLOps direction.
Resume upon request
Position: ML engineer (NLP)
Category: Data Science
Experience: 0.5 years | English: pre

Building  big web project (CRM/search/parsers) from scratch
Management team of several peoples.
Finished UCU (Master Degree in Data Science).
I am software developer using python/php. I have experience in building backend services/parser. But currently I interesting in Machine Learning, NLP and deep learning.
I took part in several competitions in Kaggle.
I finished Master Degree in UCU. Currently I work in master degree diploma (NLP, summarization task)
I passet Stanford NLP course (CS224n).
complex projects
interesting peoples
Position: ML Engineer / R&D / MLOps
Category: Python
Experience: 4 years | English: fluent

Created hyper-parameter optimization system from scratch.
During this period, solved in a creative way several problems and these solutions are under publication in scientific conferences.
Past experience.

Research Assistant and Software Engineer in Technische Universität Dresden.
March 2018 - July 2020
• Hyperparameter optimization framework was developed from scratch and later turned into a Software Product Line (SPL) with a micro-services architecture;
• Performed architectural, work-flow, design decisions and code review;
• Main component-wise developments: Repetition manager (see publications below); surrogate models; optimization algorithms; reinforcement learning-based solver selection and its parameter control; benchmarking service;
• Used technologies: Python, Sklearn, Statsmodels, Pandas, Seaborn, RabbitMQ, WebSocket, Flask, Pytest; Bash, Docker, K8s, Jenkins;

Quality Assurance Engineer in Tyco International Ltd., Elpas Project
November 2016 - September 2017
• Improved the server stability by planning, executing and analyzing stress and performance tests;
• Deployed monitoring system; gathered and visualized server performance metrics; participated in the development and bug-fixing process;
• Used technologies: VMware ESXi, Zabbix, Python, Locust, PyQT, JMeter, Bugzilla, JIRA

Technical Support Engineer in ISP "Wnet"
June 2015 - June 2016
TECHNICAL SUPPORT ENGINEER
• Network monitoring, diagnostic and debugging; L2-L3 network equipment and servers configuration;
• Technical support of a corporate segment of the company; Management and leading support team;
• Used technologies: Bash, Nagios monitoring system, Networking (DNS, DHCP, OSPF, BGP, TLS/SSL, STP, IP)


I am Interested in Data Science and Machine learning-related R&D position in a company with experienced colleagues. Why experienced? First of all, I am eager to study more, to share knowledge, and to grow as a specialist. Next, I am sure that participating in the creation of an interesting and demanded product is a key to drive creativity and willing to improve it within team.
Mostly interested in R&D which implies large (commonly) product projects with new technologies. I do like also software architecture-related tasks and already have some experience here.
Position: ML Engineer/Researcher
Category: Data Science
Experience: 4 years | English: fluent


- Classification;
- Clustering;
- Recommendation systems;
- Predictive analytics;
- Time series;
- NLP;
- Writing data pipelines, CI/CD;
- Working at all stages of the DS pipeline.
- NOT supporting genocide by paying taxes to russian government;
- Medicine/Life Science domains;
- NOT CV;
- Machine Learning positions (NOT backend, frontend, etc);
- Research position (with engineering <=50% of time);
- Non-trivial tasks/algos/ideas;
- Existing ML/DS team (NOT first ML person in the company);
- Flexibility/personal growth and development;
- Responsible AI.