Tech Lead and System Architect with over 12 years of experience in software development and team leadership. Throughout my career, I’ve built development departments from scratch, led cross-functional teams of up to 60 people, and overseen projects involving complex architecture and high-load systems.
I’ve designed and implemented data platforms exceeding 300 TB in scale, and developed payment systems with over 2 million daily active users and more than 5,000 transactions per second. My focus areas include backend development, data engineering, and system architecture.
I work confidently with Python, Django, PostgreSQL, Greenplum, Kafka, Airflow, Docker, and RabbitMQ. I’m deeply involved in pre-sales, architecture planning, mentoring junior specialists, and aligning tech solutions with business strategy. I thrive in environments where I can combine technical depth with long-term thinking and team growth.
An AI engineer and robotics enthusiast passionate about bringing technology to life—literally. I specialize in integrating machine learning with robotics, always striving to build devices that feel less mechanical and more human. My projects, like the cheerful Roboista barista robot, reflect my belief that the best technology doesn’t just solve problems—it makes you smile along the way.
Created Roboista, a witty barista robot who serves coffee with a dash of humor and personality. Roboista uses computer vision to identify customers, machine learning to remember their coffee preferences, and natural language processing to engage in cheerful banter. Built on a Jetson Nano platform, Roboista combines TensorFlow Lite for real-time customer interaction and Arduino-driven robotics for precise brewing operations. The robot didn’t just improve the cafe’s efficiency—it became a beloved community figure, boosting both sales and smiles.
Developed PlantBot, an AI-powered gardening assistant designed for busy city dwellers. Using a Raspberry Pi, sensors for soil moisture and sunlight detection, and an ML model trained on plant health datasets, PlantBot proactively alerts users when their beloved houseplants need care. With cheerful notifications like “I’m thirsty—your fern speaking,” PlantBot has humorously saved countless houseplants from neglect, turning plant care into an engaging, enjoyable experience.
I’m an engineer obsessed with space—probably because Earth ran out of problems challenging enough. For over 15 years, I’ve combined my love for robotics, AI, and questionable jokes to build tech that survives the harshest space conditions—even Mondays.
Tired of space suits getting torn by sneaky meteorites, I developed AstroWeaver, a self-healing suit fabric that patches itself faster than you can say, “Houston, we have a problem.” Microcapsules filled with adhesive polymers burst open at the first sign of trouble, repairing damage instantly. Because who has time to sew in zero gravity?
I designed MarsHab, a spacecraft habitat module built for long-haul trips to Mars. It comes packed with intelligent thermal management, advanced radiation shielding, and an AI-based life-support system that constantly adjusts conditions—because manually setting a thermostat 140 million miles from home gets tricky. MarsHab is so comfy, some astronauts joked they’d rather stay in orbit than deal with Earth traffic again.
Frontend Architect & Angular Expert with over 10 years of experience delivering responsive, high-performance web applications and mobile solutions. With a foundation in C programming, microchip design, and data transmission, I bring a deep understanding of systems to the frontend world—especially Angular, which I’ve been working with since its early days.
I've led cross-functional teams, driven architectural decisions, and delivered end-to-end projects from concept to production, including app migrations, SEO optimisation, and UI/UX design. My work spans industries from CRM and payments to social platforms and e-commerce.
Known for my eye for detail and performance, I focus on creating seamless, scalable experiences—whether it's boosting Lighthouse scores, integrating Stripe, or mentoring teams on Angular best practices.
Architect & Principal Software Engineer with 12+ years of experience designing and building scalable systems, primarily within the .NET ecosystem. Proven track record of leading cross-functional teams, evolving system architecture based on microservices, and optimising infrastructure and development processes. Skilled in building high-load systems, integrating service metrics, and automating CI/CD pipelines. Experience spans industries from fintech to enterprise software, with deep hands-on expertise in .NET 6–8, Kafka, Kubernetes, ElasticSearch, RabbitMQ, and both SQL and NoSQL databases. Passionate about solving complex engineering challenges and driving long-term technical strategy.
Data Analyst with 2.5 years of experience in building reporting and visualisation solutions using Power BI, Looker Studio, and Visiology.
Proficient in writing complex SQL queries across ClickHouse, Greenplum, and Google BigQuery, with hands-on experience developing data marts in GP and GBQ. Skilled in automating data workflows and creating dashboards with Python. Actively studying modern AI methods with a solid foundation in classical machine learning algorithms. Academic background includes designing data models (star/snowflake schemas) and implementing triggers and transactions.
With my extensive 7-year background as an iOS engineer, I've demonstrated deep expertise in Apple's iOS platform, mastering both SwiftUI and UIKit. My engagement with various architectural patterns, especially my current focus on the Composable architecture, showcases my adaptability and forward-thinking approach in software development.
As an iOS developer in FG BCS, a leading investment company in the Russian market, I contributed to their app for private investors. We wanted to enable our users to top up the card balance with Apple Pay. There was no direct way to implement this flow, so we had to leverage a third-party service that created an order for the refill amount and transferred the payment to the client’s card using our API. The transaction processing and balance renewal on the screen were imitated.
As an iOS developer in FG BCS, a leading investment company in the Russian market, I contributed to their app for private investors. User was able to enter parameters of an account or a card they wanted to create (currency, type, name, etc) and after confirmation refill it from another card, account or with Apple Pay
Created and developed the application logic for bank product calculators (credits, savings, etc.) from data layer to presentation layer.
Product Manager with 4 years of international experience across the EU, US, and Asia, specialising in fintech and marketplaces. My background spans both B2B and B2C sectors, with a focus on enhancing usability, managing integrations, and driving growth through product-led strategies for web and mobile platforms.
The admin side of our service was outdated, lacked cohesiveness due to the initial desire to accelerate time to market, and there were constant complaints about things being hard to find there and simple tasks taking hours. Our business development managers also noticed that users often required personal help with onboarding during calls and wrote mailed similar questions to our support, which meant spending extra time and money. I led the redesign of 14 sections of the personal account, including the payment history, invoices/donations pages, mass payouts, balance top-up/withdrawal, wallets management, and various integrations.
Leveraged best practices to ensure seamless and quick sign-up and onboarding for new users.
Leveraged and combined several payment management systems in the mobile app to receive the desired payment flows: user-platform-user, user-platform-merchant, merchant-platform-user. Optimised the usage of 3rd party APIs and their sequence to receive the lowest possible fee.
Led the creation of an admin panel for a new social media startup from scratch. Took part in creating the project documentation, design, backend and frontend services with a product team. We created the means to manage content and its categories (with a 3rd party tool that helps moderation + the work environment for human moderators), users, payments (payment history, integrations dashboard), notifications, and editorial pages.
We implemented automatic certificate generation for course participants, a webinar platform, a new access control system for course modules, and enhanced the pricing model. By identifying and fixing an error that was blocking payments for a specific user segment, we increased the conversion rate to paid plans by 20%.
I am a enthusiastic and results-driven Corporate Development Manager, who is committed to businesses by creating valuable products and services with global impact. With a wealth of experience in M&A and Strategy development, and a diverse background from investment banking, VC, and e-commerce, I bring a unique blend of skills and expertise to every project I handle.
◦ Led a portfolio of more than 8 consulting projects and M&A transactions with a combined value of over $120 million ◦ Facilitated a strategic partnership between a Fortune 100 FMCG company and an Eastern European coffee producer, resulting in a doubling of the distribution chain ◦ Prepared exit strategy from a FinTech portfolio business into a leading financial ecosystem with a 3x value growth ◦ Directed a cross-functional team of 6 to develop and implement a 5-year fashion category strategy for a leading Eastern European marketplace to reach top positions in fashion e-commerce ◦ Established a new partnership pipeline with 5 non-competitors, resulting in 8 prospective leads over a 3-month period ◦ Provided ongoing support to the leadership team, including shareholders and the CEO, through comprehensive research and ad-hoc strategy development
◦ Developed and implemented a B2C service for high net worth individuals in the asset management sector from scratch by using product approach and successfully acquired 3 clients ◦ Developed the Russian market expansion strategy for a Swiss technology company and achieved 7% quarterly growth ◦ Created a digital product strategy that increased customer portfolio by 25% for Eastern European investment company
Machine Learning Engineer with a passion for creative problem solving by combining logic and technical skills with unconventional approaches. My most recent projects, reinforced my skills in data analysis, data pre-processing and model selection/creation utilizing technologies such python, tensorflow, pytorch, and scikit-learn.
With extensive team discussions I employed three distinct methodologies, namely the Vader sentiment analysis, Bag of Words, and a Hugging Face BERT language model, for the purpose of tweet classification into two categories: "Disaster Tweets" and "Non-Disaster Tweets.". Using BERT-based language models, natural language processing (NLP), data analysis, TensorFlow, and Python programming, i made an in-depth evaluation to determine the optimal approach for the given task.
In collaboration with a fellow Data Scientist, we developed a powerful machine learning model. This model proved to be highly effective in analyzing medical data and accurately predicting whether a patient had a medical condition, achieving a remarkable accuracy rate of over 90%. Using Machine Learning and TensorFlow we facilitated the model's development. Data Analysis and Data Visualization techniques enabled us to gain valuable insights from the medical data, while Python played a pivotal role in implementing and fine-tuning the model, resulting in its impressive predictive accuracy.
Achieved an 80% accuracy rate in classifying celestial objects as Stars, Galaxies, or Quasi-Stellar Objects using a machine learning model that analyzes solar data. It was done through Data Collection, Data Preprocessing, Model Optimization, Iterative Improvement and Documentation.I Gathered a comprehensive dataset of solar data, including various features and attributes. I then Cleaned the dataset by handling missing values and outliers. Further Chosing appropriate machine learning algorithms for classification tasks and then Fine-tune hyperparameters of the model using techniques like grid search or random search to improve its performance. Lastly, Documented the entire process, including data sources, preprocessing steps, model architecture, and results, to facilitate reproducibility and collaboration.
I have significant experience in Data Analysis, good at highlighting problem issues and advising their resolution. Based on Data, I am able to explain and to implement research results. I am considering a position of a Senior Analyst in English speaking companies (and Lead position in Russian speaking). My English level is intermediate, but I’m improving it.
Led the shift of analytical infrastructure, enhancing data resources and decreasing update errors by 90%. Increased identifiable traffic sources from 60% to 95%. Played a crucial role in reducing fraudulent responses from 28% to 1-4% by strengthening moderation and creating a fraud analytics direction. Contributed to a project reducing the cost of applications from groups by 70% and reducing vacancies in central Moscow from 20% to 6%.
Developed an integrated automated online and offline sales analytics system, utilizing various tools like GA, ExpertSender, Dynamic Call Tracking, Naumen, and 1C. Reduced BigQuery costs by over three times and improved the effectiveness of advertising campaigns by 8-10%.
Accomplished analytics professional with 28 years of diverse international experience, a track record of successfully transforming business analytics into an efficient end-to-end Big Data process, and a strong desire to make a difference through the discovery of smart analytical solutions.
Over 6 years’ experience in Machine Learning and A.I., in all three main specializations, general machine learning, natural language processing and computer vision, with a focus on general machine learning and natural language processing. Experience gained in both research and product projects, while working for companies of renown such as Oracle and Deutsche Bank. Responsible for delivering state of the art A.I. solutions across the globe, in Europe, USA and Asia. Master’s degree in Artificial Intelligence.
In the corporate sector, text data flows swiftly, emanating from diverse sources in various formats, destined for multiple endpoints and actions. This continuous stream of data necessitates management through structuring, making it easy to interpret and analyse, and ultimately directing it to the appropriate user or applying the insights obtained. I utilised several large language models (LLMs) streamline and enhance this process:
In the dynamic realm of banking, ensuring effective anomaly detection is paramount. Utilising my expertise in state-of-the-art ML algorithms and advanced Deep Learning techniques, I tackled this imperative at Deutsche Bank, a globally recognized leader in financial services. The solution involved several critical stages:
Market research is a domain teeming with diverse data types, including tabular, audio, and particularly text. This wealth of data can be utilised not only to enhance internal processes through automation but also to equip the end client with valuable new functionalities and use cases.
Highly motivated, enthusiastic, and adaptable individual with valuable experience in project management and academic research, specialising in digital audio. Capable and effective in practical technical roles within the entertainment industry, including organisational and interpersonal aspects of high quality theatre production and live events. Skilled in working with clients to produce brief and deliver creative solutions through implementation of technical infrastructure.
Over the last two years, I've been dedicated to promoting the integration of AI among scientists at the globally acclaimed marine research institution, Plymouth Marine Laboratory (PML). PML's core research program is focused on critical areas such as climate change, marine pollution, and sustainability. In a recent research study published in July 2023, I developed Machine Learning approaches to ascertain the primary factors influencing the phytoplankton carbon-to-chlorophyll ratio in the Atlantic Basin.These methods provided valuable insights into the environmental factors affecting phytoplankton carbon and chlorophyll levels in the corresponding figures.
With a 9-year tenure as a freelance Audio Technology Consultant, I crafted a wide array of technical solutions. These encompassed the development and implementation of new real-time audio effects for Arm Cortex M4 hardware, the creation of VST plugins with the JUCE framework, the design and integration of a real-time processing system using Beagle Bone Black and the Bela realtime platform, as well as contributions in musical sound synthesis and Machine Learning consultancy for an interactive musical project.
✅ 4 years of being CTO in a few startups, including https://takzyli.pl. ✅ 6 years of programming experience (Python and others) ✅ Over 2 years of cutting-edge experience in the field of AI development ✅ Been at the forefront of Large Language Models since the very beginning of their boom.
Dating apps, while popular, had users spending excessive hours daily, leading to notable frustration. Research from smalltalks.ai indicated that the average daily usage was a substantial 1.5 hours, with a staggering 70% of users experiencing anxiety post-use. To address this, I developed an application powered by the advanced GPT-4 artificial intelligence. This AI not only mimics human interaction but crafts initial messages based on individual profiles, engages in meaningful conversation, and establishes emotional connections using a meticulously curated pick-up database. Once a rapport is established, it proposes a real-life meeting and notifies the human user, thus streamlining the dating process while reducing user stress.
As CTO at PrimerAI, I developed an intelligent platform for personalized cosmetics suggestions using ML and AI, including OpenCV, GPT-4, and K-means clustering for skin tone detection and categorization. I employed a holistic approach in developing and implementing this web app, which analyzed users' skin tones using computer vision and unsupervised ML algorithms. My contributions covered all aspects of the project, including designing and building the frontend and backend of the web app, as well as administering Linux servers. This ensured a seamless, end-to-end product experience that catered to our users' needs.
GregTraider is a streamlined framework designed for automated online trading and trading strategy backtesting using historical data. It simplifies the process by allowing users to write a single strategy for both backtesting and online trading, eliminating the need to rewrite and adjust strategies for different platforms. The primary benefit of using Gregtraider is that you only need to write and adjust your trading strategy once for backtesting, and it is immediately ready for real trading. This saves you the tedious work of rewriting and testing your strategy multiple times.
At WildFoundry, I held the role of developer advocate, producing educational programming content through articles and YouTube videos while offering client support. A prominent GPT use case from my experience involved analyzing the apps that users ran on their devices. To overcome the challenge of manually examining tens of thousands of users, I developed a script that scraped user pages one by one and analyzed the content via the GPT API before storing the results in a pandas dataframe. This approach enabled an unbiased and comprehensive analysis of user applications, yielding accurate numbers and insights that outperformed traditional survey methods. The ensuing report allowed the identification of target customer groups and guided the company in shaping its customer relation strategy.
In this project, I focused on implementing small open-source models, such as Zephir-7b, on single-board computers like the Raspberry Pi. This setup enabled the creation of a robot controlled by an LLM. Working with such compact models presents numerous challenges; one significant issue is the reduced level of intelligence compared to larger models like GPT-4. To address this, the project required fine-tuning the open-source LLM to achieve satisfactory results.
Motivated data scientist with 4 years of experience with Time Series and NLP models. Highly skilled in machine learning, data visualization, DevOps and creative thinking.
Over a three-year period, we worked closely with one of Russia's largest banks to successfully establish a robust AI monitoring system. This system operates with precision to swiftly address system failures by pinpointing their root causes and making well-informed decisions. The model expanded the scope of forecasted indicators to a total of 50,000, achieving an 85% reduction in false positive alerts. It also delivered a 20% improvement in precision compared to previous methodologies.
Led a team to develop an AI monitoring system that was capable of detecting anomalies in various business indicators. By closely working with one of Russia's largest banks over a span of 3 years, we designed and implemented an advanced backend system dedicated to the detection of anomalies across a wide spectrum of critical business metrics. This system significantly decreased the time and effort previously invested in manual incident detection and enhanced operational efficiency.
I coordinated a team in the development of two distinct automated incident detection models, which yielded substantial improvements in incident detection times, reducing them by an impressive 5 to 15 minutes. These models played a pivotal role in streamlining processes and optimizing the bank's operations.