Position: Lead / Head Machine Learning
Category: Data Science
English level: fluent
Years of experience: 11


With 11 of experience in commercial software development and 7 years in the field of machine learning, I have also spent 4 years as a team lead, managing a team of 4 people. My experience spans from working in large corporations to fast-paced startups from its foundation.

My main areas of expertise include:
  - Computer vision.
  - Natural language processing and understanding.
  - Reinforcement learning.
  - Quantitative research.

As a machine learning lead from August 2020 to June 2022, I mentored and led a team of three engineers from the company's foundation to its first customers. I defined architecture and the models for NLP and CV training to detect Personal Identifiable Information (PII) in documents such as text, PDFs, and images. I established the project architecture for the ML services and managed end-to-end feature deployment and testing on Kubernetes clusters.

During my time as a machine learning lead from September 2018 to August 2020, I worked on motion planning (3D navigation) problems on robotic devices. My responsibilities included planning the roadmap, assigning tasks, mentoring, making project presentations, and defining the code architecture. I researched and improved deep reinforcement learning (RL) algorithms, trained deep RL agents in simulation environments such as Habitat and MINOS, and deployed trained motion planning agents on robotic devices. In addition, I was an invited speaker at the 2019 CVPR workshop, recognized as one of the top performers in the Habitat 2019 challenge held by Facebook AI (Meta).

From June 2016 to August 2018, I worked as a machine learning engineer in Kyiv, Ukraine, where I focused on computer vision problems. My work included training object detection and classification deep learning models, such as Faster RCNN and Inception-ResNet-v2. I also trained instance-aware segmentation deep learning models, such as Fully Convolutional Instance-aware Semantic Segmentation, and mentored interns.