AI Researcher

Responsibilities

• Research and design novel AI architectures such as alternatives to standard Transformer designs, long-context models, and hybrid architectures
• Explore architectural improvements for scalability, efficiency, and stability
• Prototype and evaluate new architectures through ablations, benchmarks, and empirical studies
• Author and co-author research papers for top ML conferences and journals
• Collaborate with engineering teams to translate research into training and inference systems
• Stay current with state-of-the-art research and identify promising directions early

Requirements

• Strong background in machine learning research with a focus on model architecture
• Publication record in ML/AI venues (e.g. NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, arXiv)
• Deep understanding of neural network architectures, sequence models, attention mechanisms, and training dynamics
• Hands-on experience with PyTorch or JAX
• Ability to reason rigorously and design clean experiments
• Comfortable working in a fast-moving startup environment

Preferred Qualifications

• Experience with non-Transformer architectures (e.g. RNN-based, state-space, hybrid models)
• Work on long-context or memory-efficient models
• Open-source research contributions
• Experience bridging research and production systems
• Background in efficient training or inference-aware architecture design