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Senior AI Platform Engineer

Candor Systems

Remote · $160k – $200k / year · Full-time · Posted 5 months ago

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About the role

We run the inference backbone for 14 mid-market SaaS companies. They build the apps — we keep their models serving, scaling, and not falling over at 3am. Our platform handles 90 million predictions a day across shared GPU clusters, and we need a senior engineer to own the next phase: multi-tenant autoscaling. Right now, each client gets a dedicated serving pod. That worked at 5 clients. At 14, it's expensive and wasteful. You'll redesign our serving layer to support dynamic resource allocation, traffic-based autoscaling, and client-level SLA enforcement — all on Kubernetes with custom controllers. The team is 6 infrastructure engineers, all senior, all remote. We don't do standups. We write RFCs, review each other's code, and ship when it's ready. If you prefer autonomy over process, you'll like it here.

Fully remote.

Responsibilities

  • Architect multi-tenant model serving infrastructure on Kubernetes
  • Build autoscaling controllers for GPU resource allocation
  • Design client-level SLA monitoring and enforcement systems
  • Own incident response and post-mortem processes for serving outages
  • Write RFCs for major infrastructure changes and lead technical reviews

Requirements

  • 6+ years in infrastructure or platform engineering
  • Deep Kubernetes expertise including custom controllers and operators
  • Production experience with GPU workloads and model serving
  • Strong Python and systems programming skills
  • Experience with AWS (EKS, EC2 GPU instances, CloudWatch)

Benefits

  • Fully remote — async-first culture
  • Top-of-market salary plus equity
  • $4,000 annual learning budget
  • No meetings culture — RFCs and async reviews

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Categories

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python kubernetes docker aws mlflow

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure AI & Machine Learning Engineers

Skills

python kubernetes docker aws mlflow airflow

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