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Member of Technical Staff - Mid-Training Infra

Job in New York, New York County, New York, 10261, USA
Listing for: Reflection
Apprenticeship/Internship position
Listed on 2026-06-26
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer
Job Description & How to Apply Below
Location: New York

About The Role

  • Design, build, and operate large-scale GPU infrastructure for high-throughput model inference and mid-training workloads.
  • Develop systems that power synthetic data generation and reinforcement learning pipelines at scale.
  • Build high-performance inference platforms capable of serving and evaluating models across thousands of GPUs.
  • Optimize throughput, latency, and GPU utilization for large language model inference and rollout workloads.
  • Build infrastructure that supports reinforcement learning pipelines, including large-scale rollout generation, evaluation, and policy improvement loops.
  • Work closely with research teams to support distributed RL workloads and large-scale model evaluation infrastructure.
  • Improve performance of model execution through kernel-level optimization, model parallelism strategies, and GPU runtime improvements.
  • Develop distributed systems that enable 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.
Ideal Experience
  • 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 working with modern inference frameworks such as 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 used for synthetic data pipelines or RL training workflows.
  • Experience debugging performance issues across GPU, networking, and distributed execution layers.
What We Offer
  • Top-tier compensation:
    Salary and equity structured to recognize and retain the best talent globally.
  • Health & wellness:
    Comprehensive medical, dental, vision, life, and disability insurance.
  • Life & family:
    Fully paid parental leave for all new parents, including adoptive and surrogate journeys. Financial support for family planning.
  • Benefits & balance: paid time off when you need it, relocation support, and more perks that optimize your time.
  • Opportunities to connect with teammates: lunch and dinner are provided daily. We have regular off-sites and team celebrations.
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