About Orbifold AI

Orbifold AI is redefining how the world builds and scales multimodal AI by pioneering intelligent data curation and workflow engines. In a world overwhelmed by noisy, fragmented data, we help Fortune 500 enterprises and next-generation AI innovators transform raw multimodal data into high-quality, business-aligned training and evaluation pipelines, purposefully built for modern AI systems.

Backed by Bonfire Ventures, Fusion Fund, and other top investors, our team has led large-scale data curation efforts and contributed to foundational models including Gemini, LLaMA, and Qwen. Now, Orbifold is creating the enterprise standard for AI-native data infrastructure, powering real-world AI deployment at scale.

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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.

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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.

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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 careers@orbifold.ai.