Member of Technical Staff

Who You Are

• You have trained real ML models
• You have hands-on experience training machine learning models, whether in deep learning, reinforcement learning, evolutionary search, optimization, or related areas.
• You are strong at systems
• You have built reliable backend, cloud, distributed, or infrastructure systems.
• You can reason about scalability, fault tolerance, orchestration, observability, and performance.
• You have research taste
• You have research experience in CS, ML, AI, or a related field.
• Publishations at top conferences like ICLR, NeurIPS, or ICML are a plus, but we care more about your ability to reason from first principles, run good experiments, and make progress on hard problems.

What You’ll Work On

• Autonomous R&D systems
• Design workflows for hypothesis generation, experiment planning, model training, evaluation, debugging, and iteration.
• The hill-climbing engine
• Build systems that search large spaces of architectures, hyperparameters, datasets, losses, and training procedures, using each result to improve the next experiment.
• Frontier AI infrastructure
• Engine the APIs, schedulers, queues, storage, and observability that run many experiments reliably in parallel across models, datasets, and GPUs.
• Recursive improvement loops
• Create systems where better models produce better experiments, and better experiments produce better models.