3D Artist and Rendering Specialist

3D Artist & Synthetic Data Specialist

📍 Location: Ankara - METU Technopolis

💼 Employment Type: Full-time, On-site

🏭 Industry: Artificial Intelligence, Computer Vision, Robotic Automation

🤖 Application Domains: Automotive, Home Appliances

🎯 POSITION OVERVIEW

We are seeking a talented 3D Artist & Synthetic Data Specialist to join our AI and Computer Vision R&D team. You will create photorealistic synthetic training data and build immersive virtual environments that power our next-generation AI models.

Working with industry-leading simulation and rendering platforms, you'll combine artistic creativity with technical expertise to generate high-quality training datasets that bridge the gap between simulation and reality.

✅ QUALIFICATIONS

Education & Core Competencies:

Bachelor's degree in Computer Engineering, Industrial Design, Digital Arts, Game Design, or related field

2-3+ years of experience in 3D modeling, texturing, or rendering

Ability to balance artistic vision with technical requirements

Strong portfolio demonstrating photorealistic 3D work

3D Modeling & Texturing Tools:

Advanced proficiency in professional texturing and material authoring software

Experience with procedural material creation and shader development

3D Modeling: Proficiency in industry-standard CAD and DCC (Digital Content Creation) tools

Strong understanding of PBR (Physically Based Rendering) workflows

Material creation, optimization, and library management

Rendering & Simulation Platforms:

Experience with modern 3D simulation and rendering platforms used in AI/ML workflows

Proficiency in professional rendering engines (production or real-time)

Knowledge of ray tracing, path tracing, and global illumination techniques

Familiarity with real-time rendering pipelines (bonus)

Technical Skills - Computer Vision & Optimization:

Understanding of camera parameters, lens characteristics, and optical principles

Lighting design expertise (HDRI, studio lighting, natural illumination)

Composition principles and camera angle variations

Knowledge of image processing fundamentals (color spaces, resolution, sensor characteristics)

Familiarity with computer vision libraries and frameworks (bonus)

Pipeline & Automation:

Experience with batch rendering and automated data generation pipelines

Scripting skills for workflow automation (Python, MEL, MaxScript, or similar)

Data formatting, organization, and version control (Git)

Understanding of dataset annotation and labeling processes

Experience with asset management systems

Personal Attributes:

Exceptional attention to detail and aesthetic sensibility

Strong problem-solving and analytical thinking

Collaborative team player with excellent communication skills

Fast learner with passion for emerging technologies

Technical documentation skills (English)

Ability to iterate based on technical feedback

💡 RESPONSIBILITIES

Synthetic Data Generation:

Create photorealistic 3D scenes and images for AI model training

Develop synthetic datasets for automotive and home appliance products

Generate variations across different materials, lighting conditions, weather scenarios, and camera angles

Build procedural content pipelines for dataset diversity and scale

Ensure data quality meets computer vision requirements

3D Asset Development:

Create high-quality 3D models and textures for industrial products

Develop and maintain PBR material libraries

Apply realistic surface details, weathering, and wear effects

Optimize assets for performance without compromising visual quality

Maintain organized asset libraries and documentation

Visualization & Simulation:

Build virtual environments in advanced simulation platforms

Design virtual camera systems and lighting setups

Optimize render settings for quality-speed balance

Create physically accurate simulations matching real-world conditions

Implement domain randomization techniques

R&D & Collaboration:

Work closely with AI and computer vision engineering teams

Understand data requirements and deliver appropriate solutions

Research and test new tools, techniques, and workflows

Contribute to continuous improvement of the data generation pipeline

Create technical documentation and knowledge base

Participate in dataset validation and quality assurance