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4 дня назад

Member Of Technical Staff (AI)

Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
onsite
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Π“Ρ€Π΅ΠΉΠ΄
middle
Английский
b2
Π‘Ρ‚Ρ€Π°Π½Π°
UK/US
Вакансия ΠΈΠ· списка Hirify.GlobalВакансия ΠΈΠ· Hirify Global, списка ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹Ρ… tech-ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ
Для мэтча ΠΈ ΠΎΡ‚ΠΊΠ»ΠΈΠΊΠ° Π½ΡƒΠΆΠ΅Π½ Plus

ΠœΡΡ‚Ρ‡ & Π‘ΠΎΠΏΡ€ΠΎΠ²ΠΎΠ΄

Для мэтча с этой вакансиСй Π½ΡƒΠΆΠ΅Π½ Plus

ОписаниС вакансии

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TL;DR

Member of Technical Staff (AI): Design, build, and operate large-scale GPU infrastructure for high-throughput model inference and mid-training workloads with an accent on synthetic data generation and reinforcement learning pipelines at scale. Focus on improving performance of model execution through kernel-level optimization, model parallelism strategies, and GPU runtime improvements.

Location: San Francisco; London; New York

Company

Reflection’s mission is to build open superintelligence and make it accessible to all.

What you will do

  • 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.
  • Improve performance of model execution through kernel-level optimization, model parallelism strategies, and GPU runtime improvements.
  • 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 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.

Culture & Benefits

  • 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.
  • 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.

Π‘ΡƒΠ΄ΡŒΡ‚Π΅ остороТны: Ссли Ρ€Π°Π±ΠΎΡ‚ΠΎΠ΄Π°Ρ‚Π΅Π»ΡŒ просит Π²ΠΎΠΉΡ‚ΠΈ Π² ΠΈΡ… систСму, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ iCloud/Google, ΠΏΡ€ΠΈΡΠ»Π°Ρ‚ΡŒ ΠΊΠΎΠ΄/ΠΏΠ°Ρ€ΠΎΠ»ΡŒ, Π·Π°ΠΏΡƒΡΡ‚ΠΈΡ‚ΡŒ ΠΊΠΎΠ΄/ПО, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡ‚Π΅ этого - это мошСнники. ΠžΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ ΠΆΠΌΠΈΡ‚Π΅ "ΠŸΠΎΠΆΠ°Π»ΠΎΠ²Π°Ρ‚ΡŒΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡˆΠΈΡ‚Π΅ Π² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β†’