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Computer Vision Scientist
Job in
New York, New York County, New York, 10261, USA
Listed on 2026-02-12
Listing for:
CTW Cayman
Full Time
position Listed on 2026-02-12
Job specializations:
-
Engineering
AI Engineer, Computer Science, Artificial Intelligence
Job Description & How to Apply Below
As a Computer Vision Scientist, you will leverage advanced techniques such as GANs and Stable Diffusion to build and optimize cutting‑edge image generation algorithms for our proprietary banner generation tools. Partnering closely with engineering teams, you will drive the integration of AI and vision systems into products, fueling global expansion of our gaming platform.
- Research, develop, and optimize image generation algorithms using GANs, Stable Diffusion, and other advanced technologies, ensuring real-world product deployment.
- Advance and integrate state‑of‑the‑art neural image assessment, object detection, and image recognition techniques into existing products.
- Collaborate with engineering teams in designing, developing, and deploying AI and computer vision systems.
- Lead concept proof (POC) preparation and execution for innovative solutions, and regularly report outcomes to stakeholders.
- Support successful POC projects through engineering launches by working cross‑functionally to drive project timelines.
- Master’s degree or above in Computer Science or related fields.
- Minimum 3 years of research or industry experience in image generation (GAN/Stable Diffusion), neural image assessment, object detection, or image recognition.
- Strong data analysis and algorithm design skills; proficient in programming languages such as Python or C++.
- Ability to independently read and understand technical documentation in English.
- Excellent team player with high self‑motivation and a passion for solving real‑world problems.
- Prior experience leading large‑scale AI/computer vision projects from inception to deployment.
- Familiarity with deep learning frameworks such as Tensor Flow or PyTorch.
- Experience working in multinational or multilingual environments.
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