Anton – Python, Django, Vue.js

A next-gen tech company in industrial automation. With their cloud platform, automation engineers can program, deploy and manage our virtual PLCs built on open, international standards. With pub-sub data architectures, Report-by-Exception, built-in zero-trust cybersecurity, they are driving the long awaited upgrade of the Industrial Automation industry.

• Created the backend system from scratch:

1. a Python modular monolith combining request/reply and event-based paradigms, featuring a REST API and Websockets;
2. three Rust microservices working via an event broker;

• Designed and implemented an RDB data model and migrations;
• Implemented business and state machine logic;
• Implemented JWT-based auth (Auth0) for the monolith and user-facing microservices;
• Deployed the system using Docker and Kubernetes;
• Deployed the message broker (NATS) and participated in its setup and configuration, including streams, leaf nodes, clusters, TLS, stream mirroring, sourcing, etc.
• Implemented occasional side projects like a REST to Modbus gateway, IEC 61131-3-compliant data transfer model in Pydantic, JSON, XML, and more.

A platform's goal is to deliver insight from the microbiome to profoundly change our understanding of wellness and even our fundamental assumptions about life on earth.

The platform transforms scientists’ journey to insights, unifying constellations of complex, multi-dimensional data (the data fabric) to explore and extract signals and networks of relationship, otherwise not detectable by humans alone.

• Designed and developed fully functional internal and customer-facing prototypes, as well as components for the microservice-based compute and data infrastructure enabling the fast delivery of these prototypes;
• Performed code review on code submitted by members of Data Science, Bioinformatics, and Anton's own teams;
• Developed internal tooling and libraries for use inside the company;
• Facilitated knowledge exchange and mutual learning across teams;
• Participated in activities focused on design, planning, and prioritization of upcoming systems and features.

This project aims to help an SMB client automate repetitive tasks, such as accounting documentation and payment system integration

The project started with several small isolated requests, such as integrating a payment system, generating some accounting documents, and other small tasks, but later these components would be merged into more comprehensive processes and solutions

• Designed and implemented functionality for document generation, payment automation via the PSP and bank’s APIs, different tools for conversion between currencies, bank details, timezones and local standards;
• Built an architecture to integrate this functionality to enable end-to-end automation for some of the client’s processes;
• Developed user interfaces for the client to use and monitor these processes (a Telegram bot and some dashboard/reporting functionality).

The client is a retail goods vendor on Amazon, and they use Amazon’s product ad placements to reach out to their potential customers. This project aims to use different rule-based and machine learning-enabled pipelines to optimize keyword placements and reach more prospects on the same budget

• Implemented and tested the client’s specifications for data processing pipelines;
• Created a user interface for the client to deploy and use the pipelines;
• Suggested a keyword clustering pipeline based on word vectors and unsupervised machine learning algorithms;
• As a concurrent task, maintained the client’s web scraper tool.

The web app allows users from anywhere in the world to pre-pay and book language lessons with the client's school. The app also notifies the school's administrators and teachers about upcoming lesson bookings automatically resolve time zones for all participants (students, teachers, and the school), features a credit card acquiring integration and a connection to G.Suite apps that the school uses for its daily operations

• Supervised the project from requirements to delivery
• Was in charge of hiring (and firing) subcontracting developers
• Prepared the developing and production environments
• Designed the back-end and front-end
• Tested the app together with the client's representatives and delivering the full scope to the client

A system to catalog hundreds of narrative reports, technical drawings, and cost estimate tables daily. The technical solution evolved throughout 3 years from simple rule-based if-this-than-that scripts to regular expressions to some machine learning functionality powered by spaCy and scikit-learn. In the end, we got a pipeline that automatically classified, re-named, bundled, and distributed hundreds of documents to intended recipients daily

• Led a team of 3 in-house and 2 freelance staff members
• Developed progressively advanced tools and scripts to classify, label, manage, and distribute the incoming documents automatically