Staff Software Engineer- Foundation Model Inference

DevHub

San Francisco (CA)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Benefits offered by this job

Annual performance bonus
Equity

Job summary

DevHub is building scalable LLM infrastructure to power large-scale inference workloads. You will work with cross-functional teams to improve reliability, latency, and efficiency of distributed AI systems in a fast-growing environment.

We seek a senior backend/infrastructure engineer with 8+ years' experience in distributed systems, scalable APIs, and cloud-native infrastructure. Expertise in ML infrastructure, GPU orchestration, and SOA is essential; PyTorch and vLLM experience is a plus.

Qualifications

  • Requires 8+ years of experience in backend or infrastructure engineering with expertise in distributed systems and scalable APIs.
  • Experience with ML infrastructure, GPU orchestration, and service-oriented architecture is essential.

Skills

Backend Engineering
Infrastructure Engineering
Distributed Systems
Scalable APIs
Cloud-native Infrastructure
Real-time Serving
ML Infrastructure
GPU Orchestration
Service-oriented Architecture
Deployment Pipelines
System Observability
LLM Infrastructure
Model Inference

Tools

PyTorch
vLLM

Job description

Build and optimize LLM infrastructure to power large-scale inference workloads for both partner and self-hosted models. Collaborate with cross-functional teams to improve the reliability, latency, and efficiency of distributed AI workloads.

Requirements:
  • Requires over 8 years of experience in backend or infrastructure engineering with expertise in distributed systems and scalable APIs.
  • Experience with ML infrastructure, GPU orchestration, and service-oriented architecture is essential.
Key Skills:
  • Backend Engineering
  • Infrastructure Engineering
  • Distributed Systems
  • Scalable APIs
  • Cloud-native Infrastructure
  • Real-time Serving
  • ML Infrastructure
  • GPU Orchestration
  • Service-oriented Architecture
  • Deployment Pipelines
  • System Observability
  • LLM Infrastructure
  • Model Inference
  • PyTorch
  • vLLM
Benefits:
  • Annual performance bonus
  • Equity
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