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Remote Senior Artist (Graphic Designer)

Turing Remote (🇹🇷 Turkey)

Remote Contract Senior

Create high-quality, character-driven visual assets and illustrations across various styles such as manga, pop art, and comics. Document artistic prompts and design workflows while collaborating with cross-functional teams to refine outputs.

Responsibilities

  • Create high-quality, character-driven visual assets and illustrations across various styles such as manga, pop art, and comics. Document artistic prompts and design workflows while collaborating with cross-functional teams to refine outputs.

Requirements

  • Requires a Bachelor's degree in Graphic Design or Fine Arts and a comprehensive portfolio demonstrating multi-style digital illustration. Proficiency in Procreate, Adobe Illustrator, and Adobe Photoshop is essential.

Key Skills

Digital illustration Character design Manga style illustration Pop art illustration Comic art Procreate Adobe Illustrator Adobe Photoshop Artistic prompt documentation Workflow design Cross‑functional collaboration Creative concept development Storytelling Visual asset creation Remote teamwork

About Turing

Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Powering this growth is Turing’s talent cloud—an AI-vetted pool of 4M+ software engineers, data scientists, and STEM experts who can train models and build AI applications. All of this is orchestrated by ALAN—our AI-powered platform for matching and managing talent, and generating high-quality human and synthetic data to improve model performance. ALAN also accelerates workflows for model and agent evals, supervised fine-tuning, reinforcement learning, reinforcement learning with human feedback, preference-pair generation, benchm

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