Research Engineer

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This range is provided by Orbifold AI. Your actual pay will be based on your skills and experience talk with your recruiter to learn more.

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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.

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.

Preferred Qualifications

Why Join Orbifold AI?

If youre passionate about pushing the boundaries of multimodal AI, wed love to hear from you!

Apply Now : Send your resume and a short introduction to careers@orbifold.ai .

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Software Development

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