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$120,000.00/yr - $250,000.00/yr

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Join Orbifold AI and shape the future of enterprise intelligence. Backed by top-tier Silicon Valley VCs and trusted by Fortune 500s and AI pioneers, we're on a mission to redefine enterprise data. We develop proprietary AI models to transform unstructured multimodal data (vision, language, and beyond) into high-performance, AI-ready data engines. Your work here will directly contribute to these models and power the next generation of cutting-edge visual and language applications, solving real-world challenges for leading organizations.

About Orbifold AI

Join Orbifold AI and shape the future of enterprise intelligence. Backed by top-tier Silicon Valley VCs and trusted by Fortune 500s and AI pioneers, we're on a mission to redefine enterprise data. We develop proprietary AI models to transform unstructured multimodal data (vision, language, and beyond) into high-performance, AI-ready data engines. Your work here will directly contribute to these models and power the next generation of cutting-edge visual and language applications, solving real-world challenges for leading organizations.

About the Role

As a Research Engineer 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 into high-quality AI 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.

• 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.

• 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.

• 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.

• Internship

• Full-time

• Engineering and Information Technology
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