Research Engineer, Core ML

📋 Description Translate RL algorithms, scheduling, and inference optimizations into production systems. Ship improvements in latency, throughput, and model quality at scale. Own end-to-end systems from algorithms to serving stacks and infrastructure. Work on high-performance inference and RL/post-training engines. Collaborate across RL, training, and deployment to ship robust frontier models. Lead technical initiatives and contribute to cross-team roadmaps. 🎯 Requirements Bias toward implementation and shipping; eager to modify real engines and services. Systems-first profile: large-scale inference systems, GPU performance, distributed serving. RL-first profile: RL/post-training for LLMs or large models. Model architecture design for Transformers or other large nets. Strong Python coding and ability to optimize across GPU, networking, memory. Track record of ML systems work; can read new RL/post-training papers. 🎁 Benefits Competitive compensation, startup equity, health insurance, and benefits.