Dias Bakhtiyarov
Verified Expert in Engineering
Python Developer
Dias is a Python software developer and AI/DS engineer with experience in deep learning, geospatial image processing, and black-box optimization. He's passionate about process automation and optimization. Dias enjoys writing clean, readable, and efficient code with scalability in mind.
Portfolio
Experience
Availability
Preferred Environment
PyCharm, Docker
The most amazing...
...thing I've developed is a high-performance distributed remote sensing data collection and processing pipeline for deep learning research.
Work Experience
Core AI Engineer
Solai
- Developed simulation engine for last-mile delivery business operations involving capacitated multi-agent vehicle routing problems with time window constraints.
- Created continuous real-time dispatcher system using deep learning technologies and meta-heuristic optimization algorithms.
- Created a discrete simulation framework with support for stochastic event-driven processes.
Back-end Maintenance Engineer
Institute of Smart Systems and Artificial Intelligence
- Developed Telegram polling bot for data labeling of Kazakh and Turkish speech corpus.
- Extracted audio and captions data from YouTube videos as part of data collection and aggregation for text-to-speech model development.
- Maintained existing services and containerized new services for smooth operation on production servers.
Back-end Web Developer and AI Engineer
Solai
- Developed an asynchronous high-performance web back end using FastAPI, SQLAlchemy, Gunicorn, Starlette, and Pydantic.
- Implemented geohashing as a caching layer for external map API calls to decrease operating costs.
- Developed a role-based access control system with a hierarchical domain structure.
Python Software Developer and ML Engineer
Egistic
- Built a core geospatial image processing pipeline for high-performance distributed provision of Sentinel-2 remote sensing imagery products to thousands of customers.
- Designed and developed a dynamic weather data acquisition system using NASA’s NOAA service.
- Created tools for automated deployment of services to production using Ansible, GitHub, and Docker.
- Developed ML-based crop yield prediction service based on terrain profile (DEM), soil type, soil pH levels, historical time-series weather data, and remote sensing imagery products.
- Built a deep learning-based model for crop field boundary delineation.
Graduate Research Assistant
Nazarbayev University
- Simulated operation of wireless sensor framework consisting of autonomous unmanned aerial vehicles (UAV) and ground-based sensors for energy-efficient seismic data collection and multi-agent routing.
- Implemented digital image correlation and image processing of soil surface deformations due to underground soil-pipe interaction.
- Implemented UAV autonomous navigation using simultaneous localization and mapping (SLAM).
Experience
Large-scale Data Acquisition and Processing Pipeline for Deep Learning Research
MY ROLE
• Developed a scalable and distributed acquisition pipeline for Sentinel-2 satellite-based multi-spectral imagery data using Celery, RabbitMQ, and Redis.
• Implemented grouped execution of chained tasks with dynamic graph structure and runtime configurability using Celery and RabbitMQ.
• Created hybrid scalable Redis disk-based results storage back end for RabbitMQ and Celery tasks.
• Implemented cloud making, temporal difference, and spectral segmentation of multi-spectral satellite imagery data using GDAL, NumPy, SciPy, and Pandas.
Transportation Management System
MY ROLE
• Developed a core back-end API codebase.
• Created a custom multi-role-based access control system with a hierarchical domain structure.
• Automated generation of input and output response body schemas for API requests using Pydantic and ReDoc.
• Made an asynchronous data access layer using SQLAlchemy, asyncpg, and PostgreSQL.
• Created asynchronous background tasks using asyncio.
• Wrote API documentation using Swagger and ReDoc.
Meteo Data Collector for Precision Farming
Education
Master's Degree in Structural, Civil, and Environmental Engineering
Korea Advanced Institute of Science and Technology (KAIST) - Daejeon, Republic of South Korea
Bachelor's Degree in Civil Engineering
Nazarbayev University - Nur-Sultan, Kazakhstan
Undergraduate Preparatory Certificate in English
University College London - London, UK
High School Diploma in Physics
Kazakh-Turking High School - Almaty, Kazakhstan
Certifications
Codility Golden Award for the Year of the Tiger Challenge
Codility
Artificial Intelligence Foundations: Machine Learning
Skills
Libraries/APIs
Pandas, NumPy, PyTorch, PyTorch Lightning, SQLAlchemy, GDAL, GDAL/OGR, LSTM, Pydantic, Asyncio
Tools
PyCharm, Celery, Docker Compose, AutoCAD, ChatGPT, Ansible, RabbitMQ, CAD, Redoc, 3ds Max
Languages
Python, Bash, SQL, Markdown, Python 3
Storage
PostGIS, PostgreSQL, Redis, Memcached, Database Structure, Amazon S3 (AWS S3)
Frameworks
Swagger, Flask
Paradigms
Data Science
Platforms
Docker, Raspberry Pi, Amazon Web Services (AWS), Amazon EC2
Other
SSH, Machine Learning, Programming, Deep Learning, Neural Networks, Data Engineering, Convolutional Neural Networks (CNN), Image Processing, Optimization, Artificial Intelligence (AI), Algorithms, Data Analysis, Computer Vision, Time Series Analysis, Trend Forecasting, Time Series, Image Analysis, Computer Vision Algorithms, OpenAI GPT-3 API, OpenAI API, Chatbots, OpenAI GPT-4 API, OpenAI, Documentation, Genetic Algorithms, Evolutionary Algorithms, Finite Element Analysis (FEA), Finite Element Method (FEM), FastAPI, Gunicorn, Starlette, OpenStreetMap, Uvicorn, MkDocs, Data Structures, Multiprocessing, Big Data, SimPy, Graph Neural Networks, DGL, Chatbot Conversation Design, Natural Language Processing (NLP)
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