Drive end-to-end dGPU platform definition and enterprise solution architecture across hardware, firmware, drivers, and ROCm software stacks.
About the role
You will evaluate underlying GPU hardware, thermals, form factors, and enterprise management interfaces while configuring AI/ML frameworks, edge orchestration platforms, telemetry, and security stacks.
What you'll do
- Drive end-to-end dGPU platform definition, evaluating trade-offs across SoC design, power delivery, thermal envelopes, board-level signal/power integrity, and form factors for server, edge, and client systems.
- Assess memory architecture requirements (GDDR, LPDDR, HBM), memory controller design, and compression techniques while optimizing high-speed interconnect topologies.
- Define hardware-level telemetry, power-monitoring, and diagnostics hooks to integrate with enterprise manageability platforms including iDRAC, iLO, and IPMI.
- Translate system architectural concepts into software requirements spanning firmware, drivers, runtimes, ROCm libraries, tools, and application layer stacks across AI, media, visualization, and simulation workloads.
- Lead hardware/software interface definition and serve as a technical escalation point during pre-silicon modeling and early post-silicon bring-up to debug cross-layer issues spanning hardware, firmware, drivers, and application software.
- Author reference architectures, sizing guidance, and tuning guides for customers, ISVs, and systems integrators, supporting application migration onto the platform.
What you'll need
- Engineering experience in dGPU/SoC platform architecture, hardware engineering, systems software, firmware, or low-level driver development used to bring new silicon to market.
- Demonstrated experience in hardware/software co-design, including defining hardware-software interfaces, analyzing system performance bottlenecks, and debugging multi-layer hardware/firmware/software issues.
- Familiarity with enterprise manageability standards (IPMI, iDRAC, iLO) and system telemetry frameworks alongside production software monitoring stacks such as Prometheus, Grafana, or OpenTelemetry.
- Hands-on experience with containerized GPU deployment and orchestration on Linux and Windows using Docker, Podman, Kubernetes, or K3s, plus cluster schedulers such as Slurm for batch and HPC environments.
- Willingness to travel domestically and internationally on an occasional basis.
Nice to have
- Knowledge of ML/AI workloads and model architectures (Transformers, Stable Diffusion, CNNs, UNet), including optimization for GPU acceleration libraries such as ROCm or CUDA.
- Hands-on experience with DirectX 12, Vulkan, ray tracing pipelines, neural rendering, or game engine performance profiling.
- Experience with pre-silicon simulation/emulation environments, server board design, or power integrity analysis.
- Experience deploying AI serving stacks (such as vLLM or SGLang) into production, scaling across nodes, and tuning throughput and latency.
- Advanced degree (M.Sc., M.Eng., or Ph.D.) in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
Skills: dGPU platform architecture, hardware software co-design, ROCm, board-level signal integrity, enterprise manageability, Kubernetes
More semiconductor jobs: AMD jobs · Hardware design jobs · California jobs
First seen in our index 0 days ago, well below the 45-day median for Hardware Systems Engineering roles.
Hardware Systems Engineering · AI ML Hardware
|
Open roles in category
1176
|
Median days since first seen
45 d
|
Category median salary (all employers)
$148k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | AMD | All employers we track in this specialty (1176 roles · 112 employers) |
|---|---|---|
| Open roles in this specialty | 33 | 1176 |
| Open roles in the wider Software, Firmware & Systems family | 384 | 6705 · 161 employers |
| Median days since first seen | 71 d | 45 d (−26 d vs this employer) |
| Median salary (USD postings) | n/a | $148k |
Skills observed across this category: dGPU platform architecture, hardware software co-design, ROCm, board-level signal integrity, enterprise manageability, Kubernetes
Who's hiring in this category
- Intel Corporation · 95 open roles · median 31 d
- KLA Corporation · 66 open roles · median 63 d
- Applied Materials · 64 open roles · median 36 d
- NVIDIA · 62 open roles · median 76 d
- ASML · 59 open roles · median 21 d
- Teradyne · 57 open roles · median 55 d
How we counted: 1176 open Hardware Systems Engineering (AI ML Hardware) roles from 112 employers tracked in the SemiconductorJobs index, counted 13 Nov 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there, and is counted in the wider Software, Firmware & Systems family row. Days are counted from when our index first saw each posting, not from the employer's original posting date.