Member of Technical Staff - Mid-Training Infra

About the job

Responsibilities

• Design, build, and operate large-scale GPU infrastructure for high-throughput model inference and mid-training workloads.
• Develop systems powering synthetic data generation and reinforcement learning pipelines at scale.
• Build high-performance inference platforms for serving and evaluating models across thousands of GPUs.
• Optimize throughput, latency, and GPU utilization for large language model inference and rollout workloads.
• Build infrastructure supporting reinforcement learning pipelines, including large-scale rollout generation, evaluation, and policy improvement loops.
• Support research teams with distributed RL workloads and large-scale model evaluation infrastructure.
• Improve model execution performance through kernel-level optimization, model parallelism, and GPU runtime enhancements.
• Develop distributed systems for large-scale synthetic data generation and RL-driven training workflows.
• Diagnose and resolve performance bottlenecks across inference runtimes, GPU kernels, networking, and distributed compute systems.

Requirements

• Experience deploying and operating large-scale GPU systems for inference or model serving.
• Several years of hands-on experience building and running production infrastructure.
• Strong understanding of GPU performance characteristics and optimization techniques.
• Experience with modern inference frameworks like SGLang, Megatron, or similar high-performance LLM runtimes.
• Familiarity with distributed reinforcement learning infrastructure or rollout generation systems.
• Experience optimizing throughput for large-scale model execution workloads.
• Experience working with GPU kernels or low-level performance optimization.
• Familiarity with infrastructure for synthetic data pipelines or RL training workflows.
• Experience debugging performance issues across GPU, networking, and distributed execution layers.

Benefits

• Top-tier compensation: Salary and equity structured to recognize and retain talent globally.
• Stock options
• Comprehensive medical, dental, vision, and life insurance
• Annual wellness allowance
• Provided lunch and dinner in the office daily
• 22 weeks paid parental leave for all new parents
• Unlimited paid time off in the U.S.
• 30 days paid time off in the U.K.
• Sponsorship support for visas and long-term immigration pathways
• Regular off-sites, happy hours, and team celebrations