3D Artist (OpenUSD & Synthetic Data)

Quick Facts

• Role: 3D Artist focused on OpenUSD and Synthetic Data for computer-vision training

Description

You will own an end-to-end synthetic data generation pipeline that produces photorealistic 3D industrial scenes for object-detection training (YOLO). The role covers creating and exporting assets to USD with correct scale, pivots, hierarchies, naming, materials, and semantic labels, maintaining a versioned OpenUSD asset library, and running SDG batches to deliver clean, training-ready datasets on schedule.

Responsibilities

• Create and model new industrial assets (equipment, vehicles, people, PPE, props, environments) in Blender

• Export to USD cleanly and consistently, ensuring correct scale, pivots, hierarchies, naming, materials, and SDG-dependent semantic labels

• Keep polycount, texture budgets, and LODs suitable for large-scale batch rendering

• Edit, repair, and extend the existing OpenUSD assets and scenes (references, payloads, variants, layering, materials, semantics)

• Validate assets before they enter the library (broken references, wrong units, missing semantics)

• Own SDG generation end to end: configure and launch batches, select scenes, apply domain randomization, and produce annotation outputs

• Monitor runs, verify output and label quality, and hand off documented datasets to the ML team on schedule

• Close the loop with ML engineers by turning underperformance into concrete asset or randomization changes and re-generating

Requirements

• 3+ years of professional 3D experience (games, VFX, simulation, archviz, or synthetic data)

• Strong Blender skills: modeling, UVs, texturing, and materials

• Hands-on OpenUSD experience, including composition concepts and debugging broken stages

• Working Python skills to run, configure, and lightly modify pipeline scripts

• Computer-vision awareness of what makes synthetic data useful for detection models (annotation types, domain randomization, sim-to-real gap)

• High ownership and disciplined, reliable delivery

• Communicative English and Polish for day-to-day collaboration

Benefits

• Mission-driven impact: datasets that help train models preventing injuries on real industrial sites

• Full ownership of 3D content and the SDG pipeline, with improvements shipping into production models

• Direct collaboration with the ML team and founders; short feedback loops

• LLM-backed co-pilot access (e.g., Claude) for Python scripting, USD debugging, and Omniverse-related work

• Workstation-class GPU and the tools you need

• Hybrid work from the Wrocław office; B2B contract with compensation matched to experience