AI Research Engineer

Videospan Labs; Full-Reuenthal; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Videospan Labs in Switzerland is seeking an AI Research Engineer to push generative video capabilities. You will move quickly from research to production, integrating diffusion models, LLMs, and multimodal systems into our video creation workflow.

You will collaborate with video engineers to optimize encoding pipelines, CUDA runtimes, and GPU inference, delivering production-ready features from research prototypes.

Qualifikationen

• MS or PhD in Computer Science, AI, or related field.
• Strong proficiency in Python and deep learning frameworks.
• Experience with generative models and computer vision.
• Familiarity with video codecs and encoding workflows.
• Ability to read and implement research papers, then productionize results.

Aufgaben

• Research and implement novel approaches for consistent character, style, and motion generation in video.
• Fine-tune open-source models for specific video production tasks.
• Optimize model inference for production environments on GPU hardware.
• Collaborate with video engineers to integrate AI outputs into FFmpeg, HLS, and rendering pipelines.
• Build automated pipelines for dataset curation, model evaluation, and continuous improvement.
• Move quickly from research spike to shipped feature in a resource-constrained environment.

Kenntnisse

Python

PyTorch

TensorFlow

Diffusion models

Computer vision

CUDA/TensorRT

GANs

Ausbildung

MS or PhD in Computer Science, AI, or related field

Jobbeschreibung

Join our R&D team to push the boundaries of generative video. As an AI Research Engineer at a late-stage seed / early Series A company, you will move fast from prototype to production, integrating state-of-the-art diffusion models, LLMs, and multimodal systems into our video creation workflow. You will work directly with video technology, encoding pipelines, and GPU-optimized inference to enable users to generate professional content from simple prompts.

What you'll do

• Research and implement novel approaches for consistent character, style, and motion generation in video.
• Fine-tune open-source models (Stable Diffusion, Llama, video diffusion, etc.) for specific video production tasks.
• Optimize model inference for production environments, balancing latency, cost, and quality on GPU hardware.
• Collaborate with video engineers to integrate AI outputs cleanly into FFmpeg, HLS, and rendering pipelines.
• Build automated pipelines for dataset curation, model evaluation, and continuous improvement.
• Move quickly from research spike to shipped feature in a resource-constrained, high-impact environment.

Requirements

• MS or PhD in Computer Science, AI, or related field (or equivalent experience).
• Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
• Experience with generative models (GANs, Diffusion Models, VAEs) and computer vision.
• Familiarity with video codecs, container formats, and encoding workflows.
• Comfort profiling and optimizing inference on CUDA, TensorRT, or similar GPU runtimes.
• Ability to read and implement research papers, then productionize the result.