O
AI Platform Engineer
Oliver Brandt
Full-time · Mid-level · New_York
About the role
50 data scientists. Every one deploys differently. Some use a shared EC2 instance. Some maintain their own containers. There is no model registry that anyone actually uses. Our goal is to build an internal AI platform that makes the right way the easy way — standardised training pipelines, a feature store that's genuinely adopted, one-click deployment. We're hiring the engineer who will own this from design through to rollout. High leverage, broad scope, real influence over how ML gets done here.
Responsibilities
- Design and build the core internal AI platform
- Build and maintain model serving infrastructure
- Develop a feature store integrated with our data warehouse
- Build developer tooling to simplify model training and deployment
- Gather feedback from ML engineers and continuously improve the platform
Requirements
- Experience building internal ML platforms or developer tools
- Strong Python and understanding of ML workflows end to end
- Experience with model serving frameworks (Triton, TorchServe, BentoML, or similar)
- Familiarity with feature stores (Feast, Tecton, or Hopsworks)
- Able to gather requirements from ML engineers and translate into platform features
Benefits
- Platform engineering at scale — high leverage
- Full remote
- Equity
- Fast-paced, engineering-led culture
- Top-tier hardware budget
Job Type
Full-time
Level
Mid-level
Language
English
Salary Range
$125,000 – $160,000
AI Expertise
MLOps & AI Infrastructure
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