Machine Learning Engineer

Develop and fine-tune large-scale foundation models for video understanding and generation (ViTs, VLMs, multimodal encoders).
Drive data for models by designing schemas, creating/curating large-scale multimodal datasets (image/video/text/edits), and building automated filters, alignment, and deduplication at production scale.
MLLM & Editing FMs: research, train, and evaluate multimodal LLMs and editing-oriented foundation models that enable creation, transformation, and in-product editing workflows.
Collaborate with extraordinary researchers and engineers to bring research ideas to production.
Stay on top of the latest ML research (e.g., diffusion models, alignment methods, multimodal understanding) and translate advances into practical solutions.
Requirements: Masters or Ph.D. in Computer Science, AI/ML or related fields; strong publication record in Computer Vision and foundational models; excellent communication skills; Python & PyTorch; distributed training; experience with Generative AI technologies (VLMs, diffusion models); hands-on experience with image/video understanding, generation and editing; experience with large-scale datasets.