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Member of Technical Staff — Performance

RadixArk· Member of Technical Staff
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Palo Alto, CA$200k - $400kfull-timePosted 5mo ago

About the role

Performance-focused role at RadixArk to push LLM inference and training systems to production-ready limits, working on latency, throughput, GPU utilization, memory efficiency, scheduling, batching, kernel behavior, distributed execution, and cost-per-token across multi-accelerator environments.

Responsibilities

  • Analyze and improve performance across SGLang, Miles, and RadixArk production deployments
  • Benchmark LLM inference and training workloads across GPUs, TPUs, and cloud environments
  • Optimize latency, throughput, memory usage, batching, scheduling, routing, and GPU utilization
  • Investigate performance regressions in real customer environments
  • Work closely with kernel, runtime, distributed systems, and product engineers
  • Build internal tooling for profiling, tracing, benchmarking, and regression detection
  • Translate customer workload characteristics into concrete performance tuning strategies
  • Help define performance metrics that matter commercially, including cost-per-token and serving efficiency
  • Partner with customers and cloud partners on deep technical evaluations
  • Contribute performance insights back to open-source SGLang and Miles

Qualifications

  • Strong systems engineering background, especially in performance-critical software
  • Experience with GPU systems, distributed systems, inference serving, ML runtimes, or high-performance computing
  • Familiarity with profiling tools, performance debugging, tracing, and benchmark methodology
  • Comfort working with Python and C++
  • Experience with CUDA, Triton, Pallas, ROCm, XLA, or kernel-level optimization is a strong plus
  • Understanding of LLM inference concepts such as batching, KV cache, prefill/decode, speculative decoding, MoE, long context, and P99 latency
  • Ability to debug messy real-world performance issues across software, hardware, and infrastructure layers
  • Strong communication skills — explain performance tradeoffs to engineers and customers
  • Prior experience with production AI infrastructure, cloud GPU environments, or open-source ML systems is a plus

Skills

Required:Systems performance engineeringGPU systemsProfiling and benchmarking toolsProgramming
Nice to have:Distributed systemsKernel/low-level optimizationLLM inference concepts
Last updated Aug 18, 2026. Interested? Apply on the company site.
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About RadixArk

SHIP AI FOR ALL

RadixArk is an infrastructure-first, deep-tech company building large-scale inference and training systems for the entire AI community.

AI systemsMilesSGLangbessemer-ai-infrastructure-2026inferenceinference-inflection-pointinfrastructureopen infrastructure
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