Graduate ML Hardware Power and Performance Engineer - Lund, Sweden
Originally posted 28 October 2026 by the employer.
About the role
This graduate role focuses on understanding and improving hardware performance and power efficiency across machine learning and neural network hardware. You will examine how architectural and build choices impact power, performance, and area across Arm IP.
What you'll do
- Characterize workloads, investigate performance bottlenecks, and analyze power consumption of hardware builds.
- Develop scripts and automation tools to support power and performance analysis.
- Examine how architectural and implementation choices impact power, performance, and area (PPA).
- Partner with engineering teams in design, verification, and implementation to analyze IP.
- Collaborate across international engineering centers on ML and neural network hardware.
What you'll need
- University degree (completed or on track to complete by start date) in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
- Foundations in programming and scripting to solve engineering problems.
- Analytical capabilities to evaluate and understand complex systems.
- Written and verbal communication skills.
Skills: power and performance, neural network hardware, workload characterization, SystemVerilog, Python
More semiconductor jobs: AI chip design jobs
This role has been open 1 day — well below the 87-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
506
|
Median days open
87 d
|
Median salary
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Arm Holdings | All employers we track in this specialty (506 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 13 | 506 |
| Open roles in the wider Software, Firmware & Systems family | 130 | 6367 · 147 employers |
| Median days open | 1 d | 87 d (−86 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: power and performance, neural network hardware, workload characterization, SystemVerilog, Python
Who's hiring in this category
- Qualcomm · 99 open roles · median 120 d
- NVIDIA · 89 open roles · median 62 d
- AMD · 32 open roles · median 112 d
- Micron Technology · 27 open roles · median 64 d
- Mobileye · 20 open roles · median 90 d
- Analog Devices · 17 open roles · median 47 d
How we counted: 506 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 29 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.