Machine Learning Engineer — AI Architecture Research

📋 Description

• Research and develop new neural network architectures (transformers and hybrids)
• Design architecture-level experiments (scaling laws, memory, compute)
• Prototype end-to-end models from research code to training-ready
• Collaborate with inference and systems engineers for deployable architectures
• Analyze model behavior, failures, inductive biases
• Read, reproduce, and extend cutting-edge research papers

🎯 Requirements

• Strong background in ML fundamentals and deep learning
• Hands-on experience implementing model architectures from scratch
• Solid understanding of attention mechanisms, RNNs, state-space models, or hybrids
• Training dynamics, scaling behavior, and optimization
• Memory, latency, and compute constraints at the model level
• Comfortable working in PyTorch or JAX

🎁 Benefits

• Work on core model architecture, not just fine-tuning
• Influence technical direction at a Series-A company
• Small, high-caliber team with fast feedback loops
• Ship research into production
• Competitive compensation with equity