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Infrastructure Engineer

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🇺🇸 San francisco, California, United States
Posted 17 Jul 2026

Location

Job description

San Francisco, CA
  • On-site
  • Full-time Compensation: $150,000–$250,000 + up to 1% equity

About The Company

A seed-stage LLM interpretability and context-optimization company building custom machine learning models that analyze and compress token contexts before they reach the underlying model — delivering roughly 50% inference cost reduction, lower latency, and higher accuracy for the enterprises and scale-ups integrating LLMs into their products. Venture-backed, with strong early traction (:1,000 customers within its first seven months).

Founded 2025
  • 1–10 people
  • Industry: AI Tools / LLM infrastructure

The Role

Own the full multi-region GPU infrastructure stack end to end as the sole infra hire — global low-latency serving, multi-cloud and on-premise deployments, reliability, and cost efficiency. Your work sits directly in the critical path of live customer traffic. This is a high-ownership, in-person role at a fast-moving early-stage team, working a 996 pace (9am–9pm, six days a week) in San Francisco.

What You'll Be Doing

  • Own the full infrastructure stack end to end across multi-region GPU deployments, major public clouds, and on-premise enterprise environments.
  • Build and maintain super low-latency GPU serving infrastructure that sits in the critical path of live customer traffic.
  • Manage multi-cloud deployments, including cloud marketplace integrations and provider relationships.
  • Design and iterate on deployment, scaling, reliability, and cost-efficiency systems as the sole infra owner.
  • Support on-premise deployments for enterprise clients and ensure performance and reliability at each site.
  • Research and adopt new infrastructure solutions continuously as the stack and customer base grow.

Tech stack: AWS, GCP, Terraform, Docker, CI/CD, GPU/ML inference infrastructure

Requirements

  • Own cloud systems serving compression API end-to-end
  • Build and operate global low-latency high-throughput GPU ML inference infrastructure
  • Work with AWS, Terraform, Docker and CI/CD
  • Have built and operated production infrastructure at a startup or larger company
  • Learn new solutions and technologies quickly
  • Improve and research infrastructure solutions continuously
  • Based in or willing to relocate to San Francisco to work in person at the hacker house
  • Willingness to work startup hours in a 996-style environment (9am–9pm, six days a week)

Green Flags
  • Quick learner who grasps products and systems fast
  • Experience building for performance and reliability at scale
  • Research and product focus mindset
  • High ownership mentality
  • Startup-minded operator who prioritizes learning and growth over work-life balance
  • GPU infrastructure experience in production
  • First infra hire at a startup
  • Background at an infrastructure company

Red Flags
  • Infra scope limited to model training pipelines only
  • 20+ years of experience with a slow-moving, process-heavy background
  • Prioritizes work-life balance as a primary requirement
  • No production infra ownership

Why Join
  • Sole infra owner with full-stack ownership from day one, directly in the critical path of live customer traffic.
  • Well-funded seed-stage company with strong early traction and an experienced backer base.
  • Significant equity, housing and food provided at the SF hacker house, visa sponsorship, laundry and cleaning, company off-sites, infinite DoorDash, and health & dental.

Details
  • Location: San Francisco, CA
  • Work policy: In person (SF hacker house); 996 pace — 9am–9pm, six days a week
  • Compensation: $150,000–$250,000 + up to 1% equity
  • Visa sponsorship: Available (H-1B, O-1, OPT)
  • Employment type: Full-time

Job details

EmployerSign in to view the employer name
LocationSan francisco, California, United States
Posted17 Jul 2026
SalaryNot specified
Work locationSan Francisco, CAWork policy: In person (SF hacker house); 996 pace — 9am–9pm…
SponsorshipVisa Sponsored ✓
Categories
Information Technology

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