Vladimir “Vlad” Karashchuk is a Technical Artist and Unity developer with experience in both large-scale AI simulation and interactive media. At Meta FAIR Labs (2023–2025), he co-authored the PARTNR benchmark publication and built custom Blender/Python tools that automated QA for 18,000+ 3D assets and 2,000+ articulated objects, reducing validation errors by 90% and doubling processing efficiency. He designed a region annotation system for 211 3D scenes and implemented PBR material upgrades across Habitat 3 environments to enhance realism and navigation for embodied AI. Previously at Worcester Polytechnic Institute (2022–2023), he developed a Unity-based mobile app teaching mechanical engineering statics, rebuilt gameplay logic to improve simulation accuracy, and redesigned UI frameworks across 16+ scenes for device consistency. He also resolved critical Plastic SCM conflicts to stabilize multi-developer workflows. Alongside professional work, Vlad has shipped 20+ game jam prototypes and is currently developing Entropy FM, a solo-built Unity action game featuring systemic combat, custom cutscenes, multi-protagonist design, and advanced pipeline tooling.…

Vladimir Karashchuk

Vladimir “Vlad” Karashchuk is a Technical Artist and Unity developer with experience in both large-scale AI simulation and interactive media. At Meta FAIR Labs (2023–2025), he co-authored the PARTNR benchmark publication and built custom Blender/Python tools that automated QA for 18,000+ 3D assets and 2,000+ articulated objects, reducing validation errors by 90% and doubling processing efficiency. He designed a region annotation system for 211 3D scenes and implemented PBR material upgrades across Habitat 3 environments to enhance realism and navigation for embodied AI. Previously at Worcester Polytechnic Institute (2022–2023), he developed a Unity-based mobile app teaching mechanical engineering statics, rebuilt gameplay logic to improve simulation accuracy, and redesigned UI frameworks across 16+ scenes for device consistency. He also resolved critical Plastic SCM conflicts to stabilize multi-developer workflows. Alongside professional work, Vlad has shipped 20+ game jam prototypes and is currently developing Entropy FM, a solo-built Unity action game featuring systemic combat, custom cutscenes, multi-protagonist design, and advanced pipeline tooling.…

Available to hire

Vladimir “Vlad” Karashchuk is a Technical Artist and Unity developer with experience in both large-scale AI simulation and interactive media. At Meta FAIR Labs (2023–2025), he co-authored the PARTNR benchmark publication and built custom Blender/Python tools that automated QA for 18,000+ 3D assets and 2,000+ articulated objects, reducing validation errors by 90% and doubling processing efficiency. He designed a region annotation system for 211 3D scenes and implemented PBR material upgrades across Habitat 3 environments to enhance realism and navigation for embodied AI.

Previously at Worcester Polytechnic Institute (2022–2023), he developed a Unity-based mobile app teaching mechanical engineering statics, rebuilt gameplay logic to improve simulation accuracy, and redesigned UI frameworks across 16+ scenes for device consistency. He also resolved critical Plastic SCM conflicts to stabilize multi-developer workflows.

Alongside professional work, Vlad has shipped 20+ game jam prototypes and is currently developing Entropy FM, a solo-built Unity action game featuring systemic combat, custom cutscenes, multi-protagonist design, and advanced pipeline tooling.

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Language

Russian
Fluent
English
Fluent

Work Experience

Technical Artist at Meta FAIR Labs
June 1, 2025 - September 18, 2025
Co-authored PARTNR Benchmark publication and automated QA pipelines for 18,000+ 3D assets and 2,000+ articulated objects, reducing validation errors by 90% and doubling dataset processing efficiency. Built Blender/Python tools that cut iteration cycles by 50% and streamlined annotation/export workflows for reinforcement learning datasets. Designed a region annotation system adopted across 211 3D scenes to improve AI navigation and object interaction. Implemented large-scale PBR material upgrades and automated texture integration to enhance realism and lighting in Habitat 3 environments.
Unity Developer at Worcester Polytechnic Institute
March 1, 2023 - September 18, 2025
Developed a mobile app for teaching statics using Unity’s physics engine (rigidbodies, joints, forces) to create 10 interactive levels. Rebuilt core gameplay logic to improve simulation accuracy and student engagement. Redesigned UI scaling across 16+ scenes for consistent layouts on mobile devices and resolved critical Plastic SCM merge conflicts to maintain stability in a multi-developer workflow.

Education

Bachelor of Arts in Interactive Media & Game Design at Worcester Polytechnic Institute
August 27, 2018 - March 7, 2023

Qualifications

Add your qualifications or awards here.

Industry Experience

Gaming, Media & Entertainment, Software & Internet, Education, Professional Services
    paper Meta FAIR Labs (via Insight Global) – Technical Artist

    Published Research: PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-Agent Tasks
    (co-author)

    For two years I worked on HSSD-Hab, a dataset enhancing Habitat 3, Meta’s open-source simulation platform for embodied AI. My focus was scaling 3D asset pipelines, automating QA, and improving visual fidelity to support large-scale AI training.

    Key Contributions

    Asset QA & Automation:

    Built custom Blender/Python tools to validate and export 18,000+ rigid assets and 2,000+ articulated objects, reducing iteration time by 50%.

    Automated collider corrections, material fixes, and URDF exports, condensing multi-step processes into single-click workflows.

    Scene & Environment Enhancements:

    Designed a region annotation system for 211 scenes, refining navigation, spatial semantics, and object interaction.

    Upgraded environments with PBR materials; automated deployment pipelines improved consistency and cut manual workload.

    Process Optimization:

    Standardized QA tracking for thousands of assets using Google Sheets + Python automation.

    Reduced validation errors by 90%, improved dataset scalability, and doubled processing efficiency.

    Impact

    My work enabled Habitat 3 to handle vast 3D datasets more efficiently, with higher visual realism and consistency. These contributions strengthened AI research pipelines while demonstrating expertise in:

    Large-scale asset management & CAD-like optimization

    Tool development in Blender/Python for automation

    Unity-adjacent workflows for interactive simulations

    Pipeline scalability for real-time 3D environments