AI Model Optimization Architect - Cork, Ireland
Originally posted 21 August 2026 by the employer.
About the role
This role leads end-to-end model transformation and optimization for LLMs, VLMs, diffusion, and multimodal models on Qualcomm inference accelerators.
What you'll do
- Architect and deliver model optimization strategies for efficient inference on Qualcomm accelerators.
- Drive graph capture and deployment using PyTorch, ONNX, and torch.compile, including model rewrites and graph-level transformations.
- Design and implement fusion kernels using DSL based approaches (e.g., Triton), enabling fused operations and performance critical algorithmic rewrites.
- Profile and optimize LLM/VLM/diffusion inference for throughput and latency across batch sizes, sequence lengths, and serving modes.
- Own transformer specific optimizations including KVcache management, decoding behavior, and long context performance.
- Architect and scale distributed inference strategies (e.g., sharding and parallelism) across multi-core and multi-device systems.
What you'll need
- Expert level expertise in PyTorch and inference focused model optimization; strong Python engineering skills.
- Hands on experience with torch.compile / TorchDynamo or related graph capture and compilation workflows.
- Deep understanding of transformer architectures, attention mechanisms, MoEs, and performance trade-offs.
- Practical experience with KVcache behavior, serving time optimizations, and memory/performance tradeoffs.
- Strong foundation in computer architecture, ML accelerators, and distributed systems.
- Proven ability to lead cross-functional technical efforts and influence design decisions.
- MS in Computer Science, Machine Learning, Computer Engineering, or Electrical Engineering, or equivalent experience.
Nice to have
- Experience developing fusion kernels using Triton or similar DSLs, and collaborating with ML compiler teams.
- Familiarity with LLM serving stacks and continuous batching systems.
- Background in numerical methods, performance/accuracy trade-off analysis, or evaluation frameworks.
Skills: AI Model Optimization Architect, PyTorch models, Qualcomm accelerators, ONNX, torch.compile, fusion kernels, LLM/VLM/diffusion inference, transformer specific optimizations, distributed inference, hardware architectures
This role has been open 66 days — well below the 89-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
507
|
Median days open
89 d
|
Median salary
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (507 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 99 | 507 |
| Open roles in the wider Software, Firmware & Systems family | 708 | 6268 · 146 employers |
| Median days open | 118 d | 89 d (+29 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: AI Model Optimization Architect, PyTorch models, Qualcomm accelerators, ONNX, torch.compile, fusion kernels
Who's hiring in this category
- Qualcomm (this employer) · 104 open roles · median 118 d
- NVIDIA · 88 open roles · median 60 d
- AMD · 32 open roles · median 110 d
- Micron Technology · 27 open roles · median 62 d
- Mobileye · 20 open roles · median 88 d
- Analog Devices · 18 open roles · median 45 d
How we counted: 507 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 27 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.