Founding Machine Learning Engineer

Strong background in deep learning and transformer architectures Hands-on experience training or fine-tuning large models (LLMs or vision models) Proficiency with PyTorch, JAX, or TensorFlow Experience with distributed training frameworks Strong software engineering skills — writing robust, production-grade systems Experience with GPU optimization: memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end

Build end-to-end training pipelines: data → training → eval → inference Design new model architectures or adapt open-source frontier models Fine-tune models using state-of-the-art methods Architect scalable inference systems Build data systems for training data Develop alignment, safety, and guardrail strategies Design evaluation frameworks Own deployment: GPU optimization, latency reduction, scaling policies Shape early product direction and build AI-powered experiences Explore frontier techniques