AI Researcher — AI Architecture Research

📋 Description

• Research, design, and evaluate novel AI model architectures beyond transformer basics.
• Investigate techniques to boost model scalability, efficiency, stability, and inference.
• Prototype architectures and validate via experiments, benchmarks, ablations.
• Publish high-quality papers for ML conferences and journals.
• Collaborate with engineers to deploy research into training and inference systems.
• Define long-term roadmap and influence next-generation AI models.

🎯 Requirements

• Strong ML research background with AI model-architecture focus.
• Publication record in NeurIPS/ICML/ICLR/ACL/EMNLP/arXiv.
• Deep understanding of NN architectures, sequence modeling, attention.
• Hands-on ML with PyTorch or JAX.
• Ability to design experiments, analyze results, and report findings.
• Comfortable in a fast-moving startup with ownership.
• Experience with non-Transformer architectures, long-context or memory-efficient models.
• Familiarity with efficient training, inference optimization, or open-source contributions.

🎁 Benefits

• Fully remote with flexibility and autonomy.
• Competitive compensation with meaningful equity.
• Opportunity to shape research direction and AI architectures.
• Support for publishing impactful research in top conferences/journals.
• Close collaboration with engineering to deploy ideas quickly.
• Highly technical, research-focused team with a collaborative culture.
• Exposure to challenging AI problems with real-world impact.