Advanced AI Workloads - Performance and Scalability Engineer

Published November 4, 2026 · Updated November 5, 2026

Pay not postedSan Jose, CAYesterday

Leads a small technical team optimizing AI inference performance on AMD GPUs, working across kernels, serving frameworks, and distributed systems.

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At a glance

Posted base pay

Not posted

Median $225K

Typical staff+ FDE payMiddle 50% of 390 postings$196K–$260K

The work

Builds what the customer runs

Balance

Mostly building
Mixed
Mostly pre-sales or support

Project stages

Pre-sales (not covered)
Proof of concept (not covered)
Implementation
Operations (not covered)

Coding: Writes production code
Builds for: External customers
Level: Staff+
Role: Technical lead

What they ask for

Tools

vLLM
SGLang
Triton
HIP
CUDA
PyTorch
RCCL
RDMA

Visa

No visa sponsorship

Less common in FDE jobs

Responsibility level: Staff+15%
Company stage: Public28%
Company size: About 5,000+ people33%
Individual contributor or manager: Technical lead45%

Share of US FDE postings that state each fact.

What you’ll do

Optimize AI inference workloads across GPU kernels, serving frameworks, and distributed systems.
Profile bottlenecks and turn kernel and systems findings into measurable performance gains.
Lead technical engagements with customers and recommend optimizations.
Integrate custom kernels into serving frameworks and upstream improvements to open-source projects.

What you’ll bring

Experience developing software in GPU computing, AI systems, or high-performance computing.
Hands-on understanding of AI serving frameworks and end-to-end workload profiling.
Ability to interpret kernel profiling data and diagnose GPU performance bottlenecks.
Experience with custom GPU kernels and multi-GPU or multi-node distributed systems.

About AMD

Designs high-performance and adaptive computing products—CPUs, GPUs, networking and embedded processors—for data centers, PCs, gaming and embedded systems.

Public · 5000+ people

View posting at AMD