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Baseten
Baseten
11 – 50 Xodimlar
H1B vizasi homiysiKorxonaSaaSSun’iy intellekt
Baseten mashinaviy o‘rganish va sun’iy intellekt ilovalarini ishga tushiruvchi kompaniyalar uchun model inferensiyasi infratuzilmasini taqdim etadi. Uning platformasi yuqori o‘tkazuvchanlikdagi inferensiya, tezkor joriy etish, avtomatik masshtablash, xavfsiz korporativ model taqdimoti va ochiq kodli modellarni paketlashni qo‘llab-quvvatlashni birlashtirib, tez va masshtablanadigan xizmat ko‘rsatish uchun yaratilgan. Baseten muhandislik hamda mashinaviy o‘rganish jamoalariga model infratuzilmasining operatsion talablarini boshqarishda yordam beradi, shunda ular muayyan sohaga mos modellarni ishlab chiqishga e’tibor qaratishi mumkin. Kompaniya sun’iy intellekt, SaaS va korporativ texnologiyalar sohalarida faoliyat yuritadi, jamoasida 11–50 nafar xodim bor.
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Kompaniyadagi ish o‘rinlari

Software Engineer, LLM Inference Platform - Baseten Hybrid

Build Baseten’s distributed LLM inference platform for AI companies. Work across Kubernetes orchestration, model APIs, routing, autoscaling, and production observability.

USAmerika Qo‘shma ShtatlariCAKaliforniyaNYNyu-YorkWAVashington
180 000 $ – 360 000 $ / yil
GibridTo‘liq stavkaO‘rta darajaSeniorTalab Qilinadigan Til: inglizchaDasturiy ta’minot muhandisiFull-stack muhandisi
KubernetesTaqsimlangan tizimlar

Tavsif

  • Build infrastructure and orchestration for large-scale distributed LLM inference, covering routing, autoscaling, scheduling, and runtime management.
  • Develop and operate Model APIs supporting structured outputs, tool and function calling, and multimodal serving.
  • Implement API versioning, request validation, usage metering, quotas, and authentication.
  • Create instrumentation for metrics, traces, and logs, along with repeatable benchmarks for speed, reliability, and quality.
  • Define strong practices for testing, release automation, and operational excellence.
  • Diagnose and strengthen production systems across Kubernetes, distributed runtimes, networking, and GPU workloads.
  • Collaborate with Inference Performance engineers and partner teams to deliver customer-facing optimizations.
  • Lead projects from architecture and deployment through monitoring and iteration informed by customer feedback.
  • Balance system performance, reliability, operational simplicity, and developer experience.

Talablar

  • Bachelor’s, master’s, or doctoral degree in computer science, engineering, or a related field, or equivalent practical experience.
  • At least three years of experience building and operating distributed systems, backend infrastructure, or large-scale APIs where reliability, latency, and scale are critical.
  • Demonstrated ownership of low-latency, dependable backend services involving rate limiting, authentication, quotas, metering, and migrations.
  • Strong infrastructure judgment, including experience with profiling, tracing, capacity planning, and SLO management.
  • Ability to diagnose performance and reliability problems across application, runtime, and infrastructure layers.
  • A strong focus on developer experience.
  • Willingness to learn new languages, frameworks, and systems, with an interest in inference engineering.
  • Excellent written communication and collaboration skills, including clear design documentation and effective cross-functional work.
  • Experience with or contributions to LLM inference engines or frameworks such as vLLM, SGLang, TensorRT-LLM, TGI, or Dynamo is a plus.
  • Deep Kubernetes experience, including operators and custom resources; familiarity with service meshes or API gateways is a plus.
  • Experience with distributed scheduling, autoscaling, or service orchestration is a plus.
  • Experience running GPU workloads in production is a plus.
  • Background in developer-facing infrastructure or APIs, or contributions to open-source infrastructure or machine-learning systems, is a plus.
  • Familiarity with observability tools, CI/CD systems, or release automation is a plus.

Imtiyozlar

  • Competitive compensation with meaningful equity.
  • For U.S. employees and dependents, full coverage of medical, dental, and vision insurance.
  • Flexible paid time off, including a company-wide Winter Break.
  • Paid parental leave.
  • Fertility and family-building support through a Carrot stipend.
  • For U.S. employees, a company-facilitated 401(k) plan.
  • Exposure to a range of ML startups, creating substantial opportunities for learning and professional networking.

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