Senior ML Infrastructure Engineer

About the Company

Rebar is building the next-generation operating system for commercial HVAC, electrical, and plumbing suppliers and subcontractors. Fresh off a $14M Series A, we are entering our next phase of growth with AI at the center of everything we build.

Responsibilities

• Design and build the CLI, SDK, and services that serve as the single front door to the ML platform
• Wire together cloud and SaaS stacks including compute providers, storage, and experiment tracking using infrastructure-as-code
• Own abstractions for compute orchestration, feature stores, model registries, and model deployment
• Build cost attribution, usage dashboards, and monitoring for production model serving (detection, segmentation, recognition, and LLM/VLM workloads)
• Collaborate with ML engineers to turn one-off scripts into self-serve platform features

Requirements

• Bachelor's degree in Computer Science, Electrical Engineering, or equivalent experience
• 3+ years of experience building production backend systems or ML platforms
• Expert-level Python proficiency
• 2+ years of experience with cloud infrastructure (AWS preferred)
• Proficiency with IaC tooling such as Terraform, AWS CDK, or Pulumi
• Hands-on experience with managed ML inference platforms like AWS SageMaker or GCP Vertex AI
• Proven track record operating inference at scale for various model types
• Experience managing model registries and versioning
• Ability to design clean, composable APIs and SDKs

Preferred Qualifications

• Experience integrating ML tooling like W&B or MLflow
• Experience with workflow orchestration like Temporal, Prefect, or Airflow
• Experience building internal developer portals
• Familiarity with GPU compute providers (Lambda Labs, CoreWeave, RunPod)
• Background as an ML practitioner