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AI Infrastructure Engineer
AI Infrastructure EngineerPlayerZero • San Francisco, CA, United States
AI Infrastructure Engineer

AI Infrastructure Engineer

PlayerZero • San Francisco, CA, United States
7 days ago
Job type
  • Full-time
Job description

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What You’ll Do

  • Own critical services end-to-end—from architecture and design reviews through deployment, observability, and SLOs.
  • Scale LLM-driven workloads : build retrieval-augmented generation pipelines, vector indexes, and evaluation harnesses that handle billions of events per day.
  • Design data-intensive systems : streaming ETL, columnar storage, and time-series analytics that feed our self-healing algorithms.
  • Optimize for cost & latency across CPUs, GPUs, and serverless runtimes; profile hot paths and squeeze every millisecond.
  • Champion reliability : automate testing, chaos drills, and progressive delivery so new models roll out safely.
  • Collaborate cross-functionally with ML researchers, product engineers, and customers to ship features that matter.

Qualifications

  • 2–5+ years of experience building scalable backend or infrastructure systems in a production setting.
  • A builder mindset — you like owning projects end-to-end and are thoughtful about data models, performance, and long-term maintainability.
  • Experience transitioning prototypes to production with an understanding of tradeoffs in reliability and scale.
  • Comfort with data engineering workflows — parsing, transforming, indexing, and querying structured or unstructured data.
  • Exposure to search infrastructure or LLM-backed systems (e.g. document retrieval, semantic search, evaluation, or prompt engineering).
  • Bonus Points

  • Hands-on with vector databases (e.g., pgvector, Pinecone, Weaviate) or inverted-index search (Elasticsearch, Lucene).
  • Experience operating GPU clusters (Kubernetes, Ray, KServe) or tuning model-parallel inference.
  • Familiarity with Go / Rust (our primary stack) and TypeScript for the occasional full-stack tweak.
  • Deep knowledge of observability (OpenTelemetry, Grafana, Datadog) and performance profiling.
  • Contributions to open-source ML or infrastructure projects.
  • Tackling the challenges of such a vast and complex industry is an enormous undertaking. We've raised a Series A funding and are backed by leading investors who share our vision to help us on this journey.

    Seniority level

  • Mid-Senior level
  • Employment type

  • Full-time
  • Job function

  • Information Technology
  • Industries

  • Software Development
  • #J-18808-Ljbffr

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