Curriculum Vitae

Dmytro Petrovskyi · ML/AI Engineer · Kyiv, Ukraine

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ML/AI engineer with 10+ years of experience delivering production systems across LLMs, computer vision, NLP, forecasting, and ML platform engineering. Core pattern: research-to-production delivery of systems that actually ship — not prototypes.

Skills & Domains

ML/AI LLMs, Computer Vision, NLP, Forecasting, Entity Resolution, Information Extraction
Infrastructure AWS, Kubernetes, Docker, MLOps, CI/CD, Microservices
Languages Python, SQL, Java
Data E-commerce, Social/Public Data, OSINT, Financial, LiDAR/3D

Experience

NielsenIQ

Senior ML/AI Engineer (Tech Lead)
Sep 2022 – Present
  • Building multi-agent code generation system for internal DSL — LLM-as-a-Judge, agent collaboration, dynamic context auto-compaction, custom orchestration
  • Compressed 300+ classification models into one via massive multitask learning — ~$100K/year cloud cost savings
  • Built LLM-based extraction system for large-scale e-commerce data — R&D-grade, fully shipped to production

Defense Tech (NDA)

ML/AI Engineer → Advisor/Consultant
Early 2022 – Present
  • Face/image retrieval system across ~3B public photos — petabyte-scale visual search
  • AI profiling pipeline: photo/name → compiled intelligence dossier across social platforms
  • Cross-platform identity resolution — merging accounts across social networks into real-world entities
  • Detection models for military objects in imagery (personnel, vehicles, equipment)
  • Large-scale text classification for detecting hostile/extremist social content

Rakuten / Rakuten Intelligence

Senior ML Engineer / Team Lead
Aug 2019 – Dec 2021
  • Forecasting systems for 10M+ consumer panel
  • Automatic information extraction for e-commerce using deep learning/NLP
  • ML platform: serving, training, and monitoring on AWS/Kubernetes/microservices
  • Team leadership: goal setting, coordination, business alignment

Whirl Software

ML Engineer / Team Lead
Jul 2018 – Aug 2019
  • Social media monitoring system for large-scale public data
  • NLP models: sentiment analysis, semantic similarity, named entity recognition
  • Integrated ML/deep learning solutions into big-data application architecture

Infopulse

ML Engineer
Mar 2018 – Jul 2018
  • Research and PoC for LiDAR / 3D point-cloud semantic segmentation

Zoral

ML Engineer
Jan 2016 – Mar 2018
  • Financial-risk ML: credit scoring, fraud detection, bank transaction categorization
  • NLP R&D: sentiment analysis engine, NER, coreference resolution

Promptlink Communications

Software Engineer
Jan 2013 – Sep 2015
  • Cable network monitoring system for modems
  • Statistical/early-ML approaches for network analytics and fault analysis
  • Low-level networking algorithm development and optimization