Research and build machine learning systems for large-scale AI inference within the AMD Research and Advanced Development (RAD) group.
Originally posted 12 November 2026 by the employer.
About the role
AMD is seeking a Staff Researcher to research and build machine learning systems, with an emphasis on large-scale AI inference, performance analysis, and system simulation. The role sits within the AMD Research and Advanced Development (RAD) group, investigating machine learning systems, AI infrastructure, computer architecture, and heterogeneous computing across hardware and software.
What you'll do
- Develop methods for efficient large-scale AI inference, targeting improvements in latency, throughput, cost, and interactivity.
- Develop simulators, emulators, analytical models, and research prototypes to study end-to-end inference-system behavior, including compute, memory, communication, scheduling, and data center-scale constraints.
- Design rigorous experiments to benchmark and profile AI workloads, validate models against measured system behavior, and identify bottlenecks, performance trade-offs, and optimization opportunities.
- Explore emerging model architectures, inference algorithms, and deployment strategies, and translate advances in machine learning systems and infrastructure into new research directions.
- Collaborate with internal product and research teams and external research institutes, communicating findings through technical presentations, publications, and recommendations.
What you'll need
- Ph.D. in Computer Engineering, Computer Science, Electrical Engineering, or a closely related field.
- Hands-on research experience, including Ph.D. research, laboratory work, internships, or work in academic or industrial research groups.
- Experience formulating open-ended research problems and working across multiple levels of the system stack.
- Demonstrated ability to validate ideas through rigorous analysis, experimentation, and quantitative performance analysis.
Nice to have
- Research or development experience in machine learning systems, particularly large-scale inference, performance modeling and simulation, distributed systems and networking, computer architecture, hardware–software co-design, or GPU and accelerator programming.
- Experience building research prototypes and using modern machine learning frameworks, GPU software stacks, profiling tools, and quantitative performance analysis.
Skills: AI inference, system simulation, computer architecture, heterogeneous computing, performance modeling
More semiconductor jobs: AMD jobs · AI chip design jobs · Singapore jobs
First seen in our index 0 days ago, well below the 108-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
467
|
Median days since first seen
108 d
|
Category median salary (all employers)
$237k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | AMD | All employers we track in this specialty (467 roles · 73 employers) |
|---|---|---|
| Open roles in this specialty | 21 | 467 |
| Open roles in the wider Software, Firmware & Systems family | 366 | 6586 · 158 employers |
| Median days since first seen | 126 d | 108 d (−18 d vs this employer) |
| Median salary (USD postings) | n/a | $237k |
Skills observed across this category: AI inference, system simulation, computer architecture, heterogeneous computing, performance modeling
Who's hiring in this category
- NVIDIA · 108 open roles · median 86 d
- Qualcomm · 94 open roles · median 133 d
- AMD (this employer) · 21 open roles · median 126 d
- Mobileye · 15 open roles · median 100 d
- Analog Devices · 14 open roles · median 49 d
- Micron Technology · 13 open roles · median 57 d
How we counted: 467 open AI/ML Hardware Engineering (AI ML Hardware) roles from 73 employers tracked in the SemiconductorJobs index, counted 12 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.