AI Researcher — AI Architecture Research

📋 Description

• Research, design, and evaluate novel AI model architectures beyond Transformers.
• Investigate techniques to improve scalability, efficiency, training stability, and inference.
• Prototype architectures and validate them with experiments, benchmarks, and ablations.
• Publish high-quality research papers for top ML conferences and journals.
• Collaborate with engineering teams to deploy research into production training and inference.
• Monitor AI research trends and identify promising directions for future innovation.

🎯 Requirements

• Strong academic or industrial research background in ML, with AI model architecture focus.
• Publication record in NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, or arXiv.
• Deep understanding of neural networks, sequence modeling, attention, optimization, and training dynamics.
• Hands-on experience with PyTorch or JAX.
• Ability to design rigorous experiments and communicate results clearly.
• Comfortable in a fast-moving, collaborative startup with ownership.
• Experience with non-Transformer architectures, long-context/state-space/memory-efficient AI systems is valued.
• Familiarity with efficient training techniques, inference optimization, and open-source contributions is an advantage.

🎁 Benefits

• Fully remote position offering flexibility and autonomy.
• Competitive compensation with meaningful equity participation.
• Opportunity to define research direction and influence next-generation AI architectures.
• Strong support for publishing impactful research in leading conferences and journals.
• Close collaboration between research and engineering, enabling rapid deployment of new ideas.
• Highly technical, research-focused team with a collaborative and innovative culture.