AI Researcher — AI Architecture Research

📋 Description

• Research, design, and evaluate AI model architectures beyond Transformers.
• Investigate techniques to improve scalability, efficiency, training stability, and inference.
• Prototype architectures and validate with experiments, benchmarking, and ablations.
• Publish high-quality research papers for ML venues and arXiv.
• Collaborate with engineering to translate research into production training/inference systems.
• Monitor AI research to identify future directions.
• Contribute to the long-term roadmap for next-gen AI models.

🎯 Requirements

• Strong background in ML research, specializing in AI model architecture.
• Publication record in NeurIPS/ICML/ICLR/ACL/EMNLP or arXiv.
• Deep understanding of neural networks, sequence modeling, attention, and training dynamics.
• Hands-on ML models with PyTorch or JAX.
• Proven ability to design experiments and analyze results.
• Comfortable in a fast-paced startup with high ownership.
• Experience with non-Transformer architectures, long-context or memory-efficient AI.
• Familiarity with efficient training, inference optimization, or production AI.

🎁 Benefits

• Fully remote with flexibility and autonomy.
• Competitive compensation with equity participation.
• Opportunity to shape research direction and influence AI architectures.
• Strong support for publishing in top conferences and journals.
• Close collaboration between research and engineering for rapid deployment.
• Highly technical, collaborative, innovative culture.
• Exposure to challenging AI problems with real-world impact.