Research Engineer – Experimental ML Systems

🚨 Research Engineer – Experimental ML Systems📍 San Francisco, CA | Onsite🧠 Early-stage AI research lab | Revenue-generatingAn AI research lab focused on alignment, interpretability, and reinforcement learning is hiring engineers to build experimental systems that study how models generalize, fail, and become misalignedThis is not a traditional ML infrastructure role focused on scaling training runsThe work is highly exploratory: designing synthetic environments, building research tooling from scratch, and running experiments to better understand model behaviorYou’ll work on:🧪 Designing synthetic RL environments for studying model behavior under distribution shift🎯 Building experimental platforms for generalization, robustness, and alignment research🔍 Studying reward hacking, deceptive behavior, and goal misgeneralization🛠️ Prototyping novel training setups and evaluation harnesses📊 Developing benchmarks that measure internal consistency - not just outputs⚡ Rapidly testing research hypotheses through code and experimentsExample areas include:🌍 Toy worlds where models develop deceptive or power-seeking strategies⚠️ Experimental systems for activation-level interventions🧠 Robustness benchmarks focused on internal reasoning patternsStrong fits often come from:✅ Experimental ML or RL research✅ Security research, adversarial thinking, or red-teaming✅ Building small research prototypes vs production systems✅ Strong engineering ability combined with curiosity and creativityPhD preferred, but the key requirement is the ability to build novel research systems from scratchThis is not:❌ Scaling frontier model training❌ Production ML infrastructure❌ Data engineering or product MLThis role is for people who want to invent new experimental systems - not optimize existing pipelinesInterested? Hit apply & Drop me a message!