Ignacy – Python, AWS, Microsoft Azure

The product is an interior visualization scanning engine to detect and recommend the best-fitting furniture from the client's database.

• Consulted for a luxury furniture provider and developed a PoC and MVP-level product;
• helped a client formulate requirements;
• Ignacy was also responsible for process organization, data scrapping, data labeling strategy preparation, ML activities strategy preparation, model training, product delivery and business communication.,

The product is remote vital signs tracking.

• Built, pitched, and proved project mission and vision;
• prepared and maintained the engineering process (Jira and Confluence reporting structure);
• implemented data processing pipelines and CI/CD structure;
• implemented feature validation engine;
• implemented complex computer vision pipelines;
• managed solution validation, code delivery, and business communication.

Module to generate synthetic frames for video frame conversion purposes.

• Carried out dataset scrapping and preparation;
• prepared metrics for training and evaluation
• tested SOTA solutions - including custom trainings;
• developed custom neural network;
• executed model training and evaluation.

Machine Learning solution to detect the defects of the railway infrastructure. The product was developed from scratch by a team.

• Ignacy was accountable for laboratory data analysis, dataset gathering tool based on railway YT videos, data augmentation process design and development, dataset transforming tool to emulate the data gathered by our sensors;
• managed machine learning model training as well.

The tool to provide route analysis (and comparison for different transportation types) between chosen points (cities / GPS coordinates).

• Ignacy was responsible for data gathering and analysis, missing data handling design, REST API design, backend engineering;
• managed client app design and development;
• combined data from various sources for the analysis (i.e., Google Maps API to get information about car routes).

The product is the chatbot for making doctors' appointments and basic patient service.

• Executed conversational data analysis, data diarization, and data preparation for STT model training;
• managed transcriptions correction environment preparation, digital signal analysis, denoise module design, and STT engine development.

Module to increase the video resolution for film industry.

• Ignacy scrapped, prepared and organized the dataset;
• prepared metrics for ML solution training and evaluation.

Engine analyzing customer queries to make them search filters for e-commerce clients.

• Made machine Learning environment preparation;
• executed SOTA model testing;
• designed the final model;
• Ignacy was also accountable for system design, data scraping, gathering, and organization, REST API design, development, deployment, and integration.