Staff Software Engineer — AI Inference Platform

CoreWeave

Singapore

On-site

SGD 180,000 - 240,000

Full time

16 hours ago
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Job summary

CoreWeave is building a Kubernetes-native inference platform that powers low-latency AI workloads at scale in Singapore. As Staff Software Engineer (IC5), you will lead architecture and reliability across multiple services, guiding cross-team initiatives and mentoring engineers.

You will optimize scheduling, batching, memory usage, and GPU utilization, working hands-on in distributed systems while shaping performance and reliability at every layer of the stack.

Qualifications

  • 8–12+ years of experience building and operating large-scale distributed systems.
  • Proven experience leading cross-team technical initiatives.
  • Strong programming skills in Go, Python, or C++.
  • Deep Kubernetes production-scale expertise.
  • Experience with low-latency, high-throughput systems.
  • Hands-on inference systems, batching, memory optimization.
  • Metrics-driven performance improvements.
  • Familiarity with BF16/FP8 and streaming workloads.

Responsibilities

  • Lead architecture and reliability across services and teams.
  • Optimize inference performance (latency, throughput, GPU utilization).
  • Influence engineering direction and drive cross-team design initiatives.
  • Work on scheduling, batching, and memory optimization in Kubernetes.

Skills

Distributed systems
Cross-team leadership
Go
Python
C++
Kubernetes
Performance optimization
GPU inference
Latency optimization
BF16/FP8

Tools

CUDA
NCCL
RDMA
NUMA
TorchServe

Job description

CoreWeave is building a Kubernetes-native inference platform that powers low-latency AI workloads at scale in Singapore. As Staff Software Engineer (IC5), you will lead architecture and reliability across multiple services, guiding cross-team initiatives and mentoring engineers.

You will optimize scheduling, batching, memory usage, and GPU utilization, working hands-on in distributed systems while shaping performance and reliability at every layer of the stack.

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