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Defcon AI
11 – 50 Angajați
Inteligență artificialăLogisticăTransport
Defcon AI dezvoltă software bazat pe inteligență artificială pentru operațiunile de logistică, transport și lanț de aprovizionare. Tehnologia sa combină modelarea software cu agenți inteligenți pentru a ajuta organizațiile să planifice și să răspundă perturbărilor cauzate de dezastre naturale, evenimente neașteptate și condiții contestate. Compania activează la intersecția dintre inteligența artificială, mobilitate și logistică și colaborează cu parteneri pentru a furniza instrumente bazate pe date, concepute să îmbunătățească reziliența operațională, procesul decizional și eficiența răspunsului.
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Locurile de muncă ale companiei

ML Engineer, Retrieval-Augmented Generation

Build scalable embeddings, vector retrieval, and grounded language-model systems for DEFCON AI’s resilient optimization platform. Deliver cited outputs, controlled rollback, and production-grade telemetry.

USStatele Unite ale Americii
165.000 $ – 200.000 $ / an
RemoteNormă întreagăNivel mediuSeniorLimbă Obligatorie: englezăInginer de învățare automată
CloudPython

Descriere

  • Scale embeddings, vector storage, and retrieval across a large evidence base with tracked provenance
  • Connect language models to source records so generated text remains citation-grounded
  • Evaluate citation errors and measure grounding quality
  • Create prompts and structured output schemas
  • Manage model packaging, version control, serving, and rollback
  • Track retrieval and generation quality, recommendation and version attribution, overrides, abstentions, grounding failures, latency, throughput, and measurement events
  • Apply bounded model assistance to challenging narrative extraction while linking every result to its source passage
  • Include recorded rule context in each model-assisted operation, with exact rule versions and ordered context
  • Operate a modular in-boundary serving path, whether self-hosted or managed, alongside the primary managed inference service
  • Ship generated explanations, scalable retrieval, dependable rollback, and comprehensive measurement telemetry

Cerințe

  • Bring at least five years of experience, including a production or near-production retrieval-augmented generation system you built yourself
  • Be prepared to explain your retrieval architecture, vector store selection, grounding tests, real-world citation failures, and rollback approach in detail
  • Demonstrate strong Python skills and hands-on experience with embeddings and large-scale vector retrieval
  • Clearly distinguish what you have shipped—prototype, proposal, or deployed code—because delivery experience matters more here than a résumé title
  • Hold US citizenship
  • Have an active US Secret clearance at the start date
  • Experience deploying models in restricted or air-gapped environments is preferred
  • Experience operating self-hosted or open-weight models is preferred
  • Experience with fine-tuning, adapters, or custom embeddings is preferred
  • Experience with federal DevSecOps, RMF, ATO, or Department of War cloud environments is preferred
  • An active Top Secret clearance is preferred

Beneficii

  • Work fully remotely in a results-oriented environment
  • Receive a competitive salary, bonus, and equity package
  • Get fully employer-paid medical, dental, and vision coverage for you and your family
  • Use unlimited paid time off with manager approval
  • Manage your schedule in a flexible work environment
  • Take 14 weeks of fully paid parental leave

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