Research Engineer - Multimodal AI

Research Engineer - Multimodal AI Los Altos, CA About Orbifold AI Backed by top-tier VCs in the Silicon Valley and trusted by Fortune 500 companies and leading AI innovators, Orbifold AI is redefining multimodal data curation and model training for enterprise AI. Our mission is to transform and augment messy multimodal data into optimized, AI-ready datasets—powering the next generation of cutting‑edge visual and language models. About the Role As a Research Engineer at Orbifold AI, you will be at the forefront of building advanced AI models and a data distillation platform that powers our multimodal AI infrastructure. Your primary focus will be developing complex visual models and optimizing AI‑driven data platforms, transforming vast, unstructured datasets into high‑quality inputs for training, RAG, and reinforcement learning. We are looking for engineers who are passionate about multimodal AI, excel in optimizing complex systems, and have a strong background in computer vision. Your contributions will drive breakthroughs in multimodal AI, expanding the capabilities of visual models and unlocking new applications across industries. Responsibilities Develop, implement, and maintain MoE models, data pipelines, batch inference operating at internet scale, processing large, multimodal datasets including images, text, and videos. Integrate the latest research methods into our multimodal models and data distillation platform, ensuring high standards of data accuracy, relevance, and diversity. Innovate and experiment with new SOTA models and data curation techniques to maximize the quality and efficiency of training advanced multimodal models. Continuously improve data & AI infrastructure to support scalability and flexibility as models and data requirements evolve. Preferred Qualifications Bachelor’s or advanced degree in Computer Science or a related field. Proficiency in Python and experience with large open source datasets like DataComp. Solid understanding of distributed computing and experience working with large-scale, high-throughput systems. Hands‑on experience with visual data and multimodal model training. Familiarity with deep learning frameworks, especially for handling multimodal data in model training. Strong interest in large‑scale visual model research and comfort working in a rapidly evolving, dynamic environment. Why join Oribifold AI? Work on groundbreaking AI research in multimodal model training and enterprise AI. Gain hands‑on experience with large-scale AI datasets and AI-native applications. Collaborate with AI leaders from Google, Meta, and Alibaba to shape the future of enterprise AI. Opportunity to contribute to real‑world AI innovations with Fortune 500 impact. Flexible work culture in a fast‑moving AI startup. If you’re passionate about pushing the boundaries of multimodal AI, we’d love to hear from you! Apply Now: Send your resume and a short introduction to View email address on click.appcast.io. #J-18808-Ljbffr Bonfirevc