Machine Learning Engineer - Computer Vision, Multimodal & Generative AI

Key Responsibilities

• Design, implement, and optimize multimodal AI pipelines that combine image, video, and generative components.
• Research and adapt state‑of‑the‑art architectures such as diffusion models and transformers for photorealistic virtual try‑on and video‑based modeling.
• Improve model controllability, compute efficiency, and scalability to meet production constraints.
• Collaborate with applied research and engineering teams to translate prototypes into robust, deployable services.
• Maintain code quality, documentation, and automated testing for all machine‑learning components.

Requirements

• Strong programming skills in Python and experience with deep‑learning frameworks like PyTorch or TensorFlow.
• Hands‑on experience building computer‑vision or generative AI models, particularly diffusion models or transformer‑based architectures.
• Proven ability to optimize models for speed, memory, and inference cost in production environments.
• Background in multimodal representation learning, handling image and video data jointly.
• Excellent problem‑solving mindset and ability to work at the intersection of research and engineering.