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Slai
Actively Hiring
Quickly build, deploy, and share machine learning models11-50 Employees
  • B2B
  • Early Stage
    Startup in initial stages

Jobs at Slai

Slai (Serverless AI) is a platform for deploying and sharing data science models. Slai packages data science models onto a fully-managed cloud environment and makes it easy for software engineers to integrate those models into their applications.
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Engineering

Product Engineer

NewPosted 1 day ago

Product Engineer

  • Building and shipping features across our Python SDK, CLI, API, and web dashboard
  • Designing a first-class experience for agents and humans
Engineering

GPU Cluster Infrastructure Engineer

NewPosted 1 week ago

GPU Cluster Infrastructure Engineer

  • Review cluster designs and bills of materials across compute, networking, and storage, and catch gaps before hardware is ordered.
  • Lead acceptance testing: validate cabling and optics, bring up the InfiniBand fabric, run burn-in, and hold vendors to their deliverables.
Engineering

Applied AI Research Engineer

NewPosted 3 months ago

Applied AI Research Engineer

  • Low-level inference optimization, from speculative decoding, quantization, KV-cache and memory management
  • Work directly with customers to optimize their production workloads, and apply your learnings to our platform as product improvements
Engineering

Distributed Systems Engineer

NewPosted 3 months ago

Distributed Systems Engineer

  • Low-level systems development: working with container runtimes, OCI image formats, and lazy-loading large files from content addressable storage
  • Efficiently packing thousands of workloads into GPUs across multiple clouds
Other Engineering

Network Engineer

NewPosted 3 months ago

Network Engineer

  • Deploy and validate data center network infrastructure (front-end, back-end, BMS, management): configure switches, install and validate optics, coordinate cabling, and drive deployments to completion.
  • Ensure physical connectivity meets production standards: coordinate fiber remediation, validate...
Engineering

Site Reliability Engineer

NewPosted 3 months ago

Site Reliability Engineer

  • Own compute fleet health end to end. Build the metrics pipelines, alerting, and unified health view that tell you the true state of every GPU in production.
  • Turn deployment debugging into an automated pipeline, not a runbook. Build and own the automation that takes a compute failure from detection through triage.