Member of Technical Staff, RL Infra

• Design, build, and optimize the infrastructure that powers large-scale reinforcement learning and post-training workloads.
• Improve the reliability and scalability of RL training pipelines, distributed RL workloads, and training throughput.
• Develop shared monitoring and observability tools to ensure high uptime, debuggability, and reproducibility for RL systems.

• BS/MS/PhD in Computer Science, Engineering, or a related field (or equivalent experience).
• Understanding of ML frameworks (PyTorch, TensorFlow, Ray, Megatron) from a systems perspective.
• Experience working with reinforcement learning workloads (PPO, DPO, RLHF, or reward modeling).
• Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.

• Experience building and maintaining large-scale language models with tens of billions of parameters or more.
• Experience with ML workflow orchestration tools (Kubeflow, Airflow).
• Background in performance optimization and profiling of ML systems.

Compensation

• Work with World-Class Talent: Collaborate with the inventors of diffusion models and leading AI researchers
• Shape Foundational Technology: Your decisions will influence how the next generation of AI products are built and used
• Immediate Impact: Join at the ground floor where your contributions directly shape product direction and company trajectory

• Competitive salary and equity in a rapidly growing startup
• Flexible vacation and paid time off (PTO)
• Health, dental, and vision insurance
• 401k match
• Catered meals (breakfast, lunch, & dinner)
• Commuter subsidies
• A collaborative and inclusive culture