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 Intern at Orbifold AI, you will be at the forefront of advancing multimodal AI models and infrastructure. Your primary focus will be on developing SOTA visual models, optimizing AI-driven data pipelines, and transforming large-scale, multimodal datasets (text, images, videos) into high-quality training inputs.

We are looking for engineers who are passionate about multimodal AI, large-scale model optimization, and data-centric AI research. You will work with MoE models, distributed systems, and batch inference at an internet scale, pushing the boundaries of training, RAG, and reinforcement learning for enterprise AI applications.

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Key Responsibilities

• Develop and optimize multimodal AI models, focusing on computer vision, NLP, and generative architectures.
• Design and maintain high-throughput data pipelines to process and curate large-scale multimodal datasets (images, text, video, structured data).
• Implement and refine MoE models to enhance model efficiency and scalability for multimodal AI training.
• Integrate the latest research innovations into our multimodal AI platform, improving data accuracy, diversity, and relevance.
• Experiment with SOTA models and data curation techniques to maximize AI training efficiency and quality.
• Collaborate with research scientists and machine learning engineers to improve data and AI infrastructure, ensuring scalability as models evolve.

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Preferred Qualifications

• Currently pursuing a Bachelor’s, Master’s, or Ph.D. in Computer Science, AI, Machine Learning, or a related field.
• Proficiency in Python and experience working with large-scale open-source datasets like DataComp.
• Strong understanding of distributed computing, HPC, and cloud-based AI infrastructure.
• Hands-on experience with multimodal model training, especially in computer vision, video understanding, and NLP.
• Familiarity with deep learning frameworks and multimodal model architectures.
• Passion for large-scale visual model research, with an ability to work in a fast-paced, dynamic environment.

Why join Orbifold 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.

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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.