Staff Software Engineer, Inference

CoreWeave; Singapore; On-site; SGD 180,000 - 240,000; Full time

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 The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com.

Staff Software Engineer, Inference

Location: Singapore

What You’ll Do

The Inference team builds and operates CoreWeave’s Kubernetes-native inference platform, powering low-latency, high-throughput AI workloads at massive scale. The team is responsible for request routing, scheduling, GPU resource management, and system-wide optimizations that drive performance, efficiency, and reliability across real-time inference systems.

About The Role

As a Staff Software Engineer (IC5) on the Inference team, you will act as a technical leader driving architecture, performance, and reliability across multiple services and teams. Your day-to-day will involve leading cross-team design initiatives, optimizing inference performance (latency, throughput, and GPU utilization), and improving system reliability at scale. You will work deeply in distributed systems and Kubernetes-based infrastructure, focusing on areas like scheduling, batching, and memory optimization. This role requires hands‑on technical leadership and the ability to influence engineering direction across the organization.

Who You Are

• 8–12+ years of experience building and operating large-scale distributed systems or cloud platforms
• Proven experience leading cross-team technical initiatives impacting multiple services or organizations
• Strong programming skills in Go, Python, or C++
• Deep expertise in Kubernetes at production scale, including orchestration, scheduling, and service design
• Strong understanding of distributed systems, networking, and performance optimization
• Experience designing and operating low-latency, high-throughput systems with strict P95/P99 latency requirements
• Hands‑on experience with inference systems, including batching or micro‑batching strategies, caching, and memory optimization
• Experience improving system performance using metrics‑driven approaches (e.g., latency, throughput, utilization)
• Familiarity with mixed precision (BF16, FP8) and streaming inference workloads

Preferred

• Experience with inference frameworks such as vLLM, Triton, TensorRT‑LLM, Ray Serve, or TorchServe
• Experience with GPU systems and performance optimization (CUDA, NCCL, RDMA, NUMA, GPU interconnects)
• Experience leading multi‑team or org‑level technical initiatives
• Exposure to large‑scale AI/ML infrastructure or hyperscale cloud environments

Wondering if you’re a good fit?

We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love to design and optimize high-performance distributed systems at scale
• You’re curious about AI inference, GPU systems, and emerging performance techniques
• You’re an expert in building reliable, low-latency infrastructure and driving system‑wide improvements

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper‑growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

About

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best‑in‑Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization’s growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

At CoreWeave, base pay is only one part of our total compensation package. Total compensation includes base salary, equity, flexible vacation policy, and comprehensive benefits. The starting salary will be determined based on job‑related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation.