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CV

Head of Machine Learning | R&D

Over 10 years of experience in statistics, scientific research, data-driven device development, and computer science. Began my career as a Junior Researcher, contributing to the development of 5 new techniques for physical and chemical analysis, creating 3 software solutions for optical control systems, and advancing physical-chemical control methods. Currently serving as Head of Machine Learning (R&D), leading a team of up to 12 people in the development of cutting-edge computer vision systems. Achieved measurable improvements, including increasing code readability from 3 to 9.2 as assessed by pylint, as well as advancing new physical-chemical control methods. These efforts have driven innovation in complex research projects, enhancing operational efficiency and product quality.

Key Skills:

R&D Strategy 100%
Computer Vision 100%
MLOps 70%
Machine Learning 80%
Data Analysis 80%
Neural Networks 70%
Team Leadership 100%

Technical Skills:

Python, FastAPI, PyTorch, OpenCV, Streamlit, Git, DVC, Docker, jupyter-hub, CVAT, ClearML, Nextcloud, GitLab, Ubuntu Server (R&D Infrastructure).

Work Experience

Head of Machine Learning (R&D) (2022 - present) Autodoria LLC, Kazan, Russia

Specializes in intelligent transport solutions, reducing road deaths by 51% and accidents by 15.6%

Responsibilities:
  1. Management of the development and training of machine learning models and data processing for computer vision projects.
  2. Setting up MLOps processes and managing Torch models for deploying and optimizing machine learning systems.
  3. Supporting R&D projects, developing and implementing research and development strategies in the field of computer vision and scene analysis.
  4. Managing 12 employees (developers and annotators) and leading an ML development team to create road scene analysis systems.
  5. Developing ML pipelines, automating, and testing model training processes.
  6. Overseeing the lifecycle management of models, evaluating market and scientific trends.
  7. Presenting solutions to senior management and clients.
  8. Preparing the research and development budget.
Achievements:
  1. Implemented an automated testing system (pytest, GitLab runners, tox) and linters (black, pylint, flake8), increasing code readability from 3 to 9.2.
  2. Introduced code review and live coding practices (weekly sessions), boosting the development team’s efficiency from 1 to 5 merge requests per month.
  3. Submitted 4 grant applications and 2 grant reports.
Machine Learning Engineer (2021 – 2022) rebels.ai, remote

Company specializing in AI and software integration

Responsibilities:
  1. Setting up and maintaining the infrastructure of 2 servers with 4 GPUs.
  2. Data preparation (climate data, satellite data: sentinel, Google Earth Engine, Nasa, ground station data: CO2, PM 2.5, PM 2.5, PM 10, industrial data).
  3. Preparation of 20 jupyter notebook (pandas, geopandas, matplotlib, sentinelhub, gee, numpy).
Achievements:
  1. Configured and maintained server infrastructure for data preparation and neural network model building.
  2. Developed 3 neural network models and actively researched neural networks.
  3. Analyzed and worked with data of up to 500 GB, optimized computations – reduced memory usage from 54 GB to 13 GB, implemented projects in climate and satellite monitoring.
Head of the Laboratory (2011 - 2022) PhosAgro inc., JSC "NIUIF", Cherepovets, Russia

Russia's only research institute specialising in phosphate rock processing technologies

Responsibilities:
  1. Managing a team of researchers (4 people).
  2. Managing laboratory infrastructure.
  3. Performing statistical analyses of data and planning experiments: development of new techniques and methods, data collection and accumulation (SCADA, MES).
Achievements:
  1. Created a team from scratch: searched for funding, selected equipment, hired staff.
  2. Created a full cycle of assembly and launch of control devices for industry.
  3. Achieved an increase in funding from 174,000 to 294,000 USD per year.
Senior Researcher:
  1. Wrote 2 software, modified 2 released software.
  2. Developed 2 prototypes of quality control devices (arduino, 3D printing, laser cut), and created methods for their analysis.
Researcher:
  1. Developed 3 new techniques of physical and chemical methods of analysis and wrote 2 software for optical control devices (PyQt5, opencv, pyserial, numpy, scipy, pandas).
  2. Developed software for optical software to control pellet composition using optical recognition.
Junior Researcher:
  1. Developed 2 new techniques of physical and chemical methods of analysis and wrote 1 software for optical control devices (PyQt5, opencv, pyserial, numpy, scipy, pandas).
  2. Developed software for optical software to control pellet composition using optical recognition.
Associate Professor, Senior Researcher (2018 - 2023) Cherepovets State University, Department of Automation and Control and Department of Chemical Technologies, Cherepovets, Russia

One of the leading research institutes in the field of mineral fertilizer production.
  1. Led research projects related to ESG, satellite data, computer vision, and analytical chemistry; supervised graduate and undergraduate student projects; managed a laboratory.
  2. Wrote 2 methodological manuals, published 5 scientific papers.

Projects

Startup LogicYield LLC (2022 — present) co-founder | MlOps engineer, remote, Russia

Startup for Optical Instruments Creation
  1. MLOps and server infrastructure (ClearML, Minio, CVAT, GitLab CI/CD, Docker Compose, FastAPI, Jupyter-hub).
  2. Developed and implemented software for industrial devices: backend and client modules (PyQt, OpenCV, scipy, numpy, pyserial, pyUSB, SQL, FastAPI, MQTT, multithreading).
  3. Created and optimized unique object segmentation models for CPU operation, published 3 scientific papers at Q1, Q2 level (CNN + Fourier, CNN + BoundaryIoU).
  4. Attracted $110,000 in investments. Successfully completed over 4 industrial tests and achieved the first sale.
Amazon forests satellite image multi-label classification and API service
Multilabel classification NN solution for Amazon forests satellite image. I made accent on "industrial quality" code with next technologies: pytorch_lightning, timm, ClearML, linters (black, isort, nbstripout, flake8), types with pydantic, DVC for local usage.
Disclaimers:
  1. the project was created by me and me only as part of the CVRocket professional development course
  2. here are a short trained version of NNs (about 15 epochs each)
Skills: Computer Vision · Machine Learning · MLOps · FastAPI · PyTorch · Neural Networks
Car Plate OCR | FastAPI | Telegram | TON
This is the project for car plate OCR recognition, which include:
  1. Neural network segmentation model for car plate area with number selection (part 1/3)
  2. Neural network OCR model for plate character recognition (part 2/3)
  3. API service for these two models (part 3/3)
  4. Additional example how to use API service in Telegram bot with TON payment possibility (The app was developed during the TON x ETH Belgrade hackathon)
Skills: Computer Vision · Machine Learning · MLOps · FastAPI · PyTorch · Neural Networks

Education

Recommendations

Timur Fatykhov | my teacher at CVRocket course
I had the pleasure of teaching Dmitrii Iunovidov in my Machine Learning (CVRocket) course at DeepSchool. Throughout our time together, I was consistently impressed by his commitment to learning, enthusiasm, and deep passion for knowledge.

As a student, Dmitrii consistently demonstrated a high level of eagerness and intellectual curiosity, actively engaging with course material. He actively participated in class discussions, asked insightful questions, and consistently produced exemplary work. This earned him a place among the top 3 graduates of the sixth cohort of the course.

Furthermore, Dmitrii brought and developed his own project for car plate OCR, which was highly regarded by my colleagues.

What truly stood out about Dmitrii was his ability to think critically and analyze complex issues. He possesses a natural aptitude for problem-solving, and his analytical skills are sure to serve him well in his future endeavors.

Marat Gilmanov | managed me directly in Avtodoria LLC
I have been working with Dmitrii Iunovidov, the Head of Machine Learning at Avtodoria LLC, since 2022. Throughout our collaboration, I have been consistently impressed by his innovative approach, strategic thinking, and expertise in developing ML content and strategy.

As the Head of Machine Learning (R&D), Dmitrii has a deep understanding of our target audience's needs and the ability to create compelling content that resonates with them. He has a natural talent for finding unique perspectives and approaches that set our content apart from the competition. Additionally, he has developed a robust and effective R&D infrastructure using Ubuntu Server, CVAT, ClearML, Nginx, Docker, and FastAPI.

Dmitrii's strategic thinking and ability to develop effective R&D content campaigns have been particularly impressive. He has a keen eye for what works and what doesn't, and has been instrumental in helping our company achieve our R&D goals.

Not only is Dmitrii skilled in his technical abilities, but he is also a pleasure to work with. He is a strong communicator and always goes the extra mile to ensure the success of our campaigns.

I highly recommend Dmitrii Iunovidov for any opportunity in the field of R&D content development and strategy. He has consistently demonstrated his ability to excel in his role. It has been a pleasure to work with him, and I am confident that he will be a valuable asset to any team or organization.

Ikechi Ndukwe | my colleague at LogicYield LLC
Dmitrii is an exceptional leader and mentor in the fields of Machine Learning, Deep Learning, and Computer Vision, applying these technologies to solve real-world problems. He is also a highly skilled MLOps Engineer. Beyond his technical expertise, Dmitrii is an experienced researcher and a dedicated team player who is always eager to support his colleagues and mentees. His guidance has been immensely beneficial to my PhD research, providing valuable insights and direction.

Working with Dmitrii has been a great pleasure, and I wholeheartedly endorse him for any position in the fields of Machine Learning and Research & Development.

Courses

Languages

  • Russian (native)
  • English (C1, proficient)
  • Bulgarian (basic)

Other

Awards
  1. Engineer of the year - Russian Union of Science and Engineering Associations, 2022
  2. 1st place in the "Innovative Engineer of the Year" competition - Vologda Region Governor, 2021
  3. Letter of Gratitude - Cherepovets State University, 2020
  4. 1st place in the corporate competition "Young Leader" at JSC "Apatit" and 3rd place throughout all "PhosAgro" Corporation - "PhosAgro" inc., 2019
  5. Letter of Gratitude - Governor of the Vologda Region, 2019
  6. Certificate of Appreciation - Russian Academy of Sciences, 2019
  7. Honorary Diploma - Russian Union of Chemists and Rosshimprofsoyuz, 2019
  8. 2nd place in the "Innovative Engineer of the Year" competition - Vologda Region Governor, 2018
  9. Letter of Gratitude - JSC "NIUIF", 2018
Intellectual properties
About me
From flasks to code: I've navigated a thrilling career journey, transforming from an analytical chemist into an innovative leader in Computer Vision. Driven by a passion for science and belief in open-source solutions, I leverage PhD in engineering, Python and PyTorch to solve complex challenges across industries. A Linux fan at heart, I feel a little uncomfortable without my computer.

I have ISSA Inshore Skipper, boat master, and car licenses and love to use them all!

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