Senior Director, Engineering Mobile Handset AI Software
$216,600 - $325,000 USD yearly
Originally posted 8 October 2026 by the employer.
Architect, develop, and optimize AI software for Snapdragon Mobile products, focusing on heterogeneous compute and LLMs/SLMs.
About the role
This role involves serving as an Embedded ML SW Architect focused on Snapdragon Mobile products, analyzing requirements and architecting high-level designs for new AI-driven use-cases and features. You will drive technical initiatives to evolve Snapdragon Mobile AI software, enhancing performance and power efficiency across SW and HW stacks and tools for machine learning solutions.
What you'll do
- Develop and recommend architecture enhancements for complex AI features and experiences on Snapdragon Mobile products.
- Independently research, define requirements, and prototype on-device agentic experiences.
- Architect context and memory management, perception (screen/scene understanding, sensor fusion), and heterogeneous compute placement for LLM/SLM workloads across CPU, GPU, and NPU.
- Serve as a technical expert, participating in design reviews and recommending improvements for business goals and customer needs.
- Influence and negotiate with external partners on project and subsystem implementation plans and milestones.
- Act as a technical expert on AI and Mobile industry trends, competitor products, and engineering advances, contributing to product/technology roadmaps.
What you'll need
- Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering, or related field and 8+ years of experience in Electrical, Computer, or Software Engineering or related work experience (or Master's with 7+ years, or PhD with 6+ years).
- 8+ years of experience in semiconductor product development.
- 5+ years in a technical leadership role.
- Extensive experience with Mobile SW architecture and deployment.
- Experience with system SW performance optimization, benchmarking, and performance breakdown analysis with CPU, GPU, NPU.
- Knowledge of AI for Computer Vision, Audio, or Generative AI.
- Hands-on experience with embedded ML at the system level on resource-constrained devices, including heterogeneous compute placement across CPU/GPU/NPU.
Nice to have
- Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch).
- Experience with large language models/foundational models and small language models (SLMs), including LoRA/adapter-based fine-tuning and on-device personalization techniques.
- Experience with agentic AI architectures (planning, tool-use/orchestration, context and memory management) and their deployment on resource-constrained embedded devices.
- Experience in architecting, designing, and implementing SW framework for complex heterogeneous or multi-processor systems, including runtime placement of ML/agentic workloads across CPU, GPU, and NPU.
- Experience with embedded ML at the system level – model deployment, scheduling, and lifecycle management under tight memory, power, and thermal constraints on mobile/embedded platforms.
- Good Understanding of complete AI Software stack and familiarity with AI hardware acceleration technologies.
- Experience with performance optimization of AI application on Windows using processor specific optimization tools/libraries/primitives on GPU, NPU.
- Experience in modeling AI networks and workloads to extract performance and power estimates, and converting that into optimization.
- Experience with context and perception pipelines (sensor fusion, screen/scene understanding, multimodal context) that power personalized or agentic on-device experiences.
- Strong background in algorithm development, performance analysis using profiling tools, and algorithmic modification methods for performance improvement.
- Knowledge of Mobile platforms, Android framework, Embedded system implementations.
- Proficiency in programming languages such as C, C++, Python.
- 10 years of experience in High-Performance Computing System Engineering or Software with 5 years in AI system optimization.
- Master's or PhD in Computer Science or Electrical Engineering.
Skills: Snapdragon Mobile AI software, LLMs/SLMs, heterogeneous compute, CPU/GPU/NPU, AI frameworks
This role has been open 0 days — well below the 48-day median for Infrastructure/Platform Software roles.
Infrastructure/Platform Software · AI ML Hardware
|
Open roles in category
110
|
Median days open
48 d
|
Median salary
$220k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (110 roles · 30 employers) |
|---|---|---|
| Open roles in this specialty | 21 | 110 |
| Open roles in the wider Software, Firmware & Systems family | 733 | 6085 · 146 employers |
| Median days open | 44 d | 48 d (−4 d vs this employer) |
| Median salary (USD postings) | — | $220k |
Skills observed across this category: Snapdragon Mobile AI software, LLMs/SLMs, heterogeneous compute, CPU/GPU/NPU, AI frameworks
Who's hiring in this category
- NVIDIA · 24 open roles · median 41 d
- Qualcomm (this employer) · 21 open roles · median 44 d
- AMD · 9 open roles · median 42 d
- Intel Corporation · 8 open roles · median 16 d
- Graphcore · 7 open roles · median 94 d
- Micron Technology · 5 open roles · median 51 d
How we counted: 110 open Infrastructure/Platform Software (AI ML Hardware) roles from 30 employers tracked in the SemiconductorJobs index, counted 9 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.