高通
Applied AI for Yield and Diagnostics, Sr. Staff
Applied AI for Yield and Diagnostics, Sr. Staff
发布于 大约 2 个月前普通员工/个人贡献者
Hsinchu City, Hsinchu City, Taiwan
高级经验
全职员工
仅现场办公
本科
研究与开发 (研发)
Diagnostics
Semiconductor
3DIC
Agentic AI
Gnns
LLM
MLOps
RAG
SQL
AI 估算 · 40k–60k
Senior AI engineer in semiconductor industry; high skill demand leads to competitive salary in Hsinchu science park.
职位详情
关于这个职位
This senior staff role at Qualcomm focuses on applying AI (Agentic AI, Knowledge Graphs, GNNs, Computer Vision) to improve silicon yield and diagnostics for advanced chips (3DIC, AI accelerators). You will architect and deploy ML solutions that interpret wafer maps, memory bitmaps, and defect images, integrating them into production workflows to speed analysis and automation. The position bridges cutting-edge machine learning with semiconductor manufacturing, requiring strong Python, SQL, and deep learning skills.
最低要求
Bachelor's degree in Science, Engineering, or related field and 6+ years of ASIC design, verification, validation, integration, or related work experience.
OR
Master's degree in Science, Engineering, or related field and 5+ years of ASIC design, verification, validation, integration, or related work experience.
OR
PhD in Science, Engineering, or related field and 4+ years of ASIC design, verification, validation, integration, or related work experience.
工作职责
Own the architecture of applied AI solutions for diagnostics and yield, from GenAI assistants to autonomous agents.
Develop and deploy ML and computer vision models that interpret wafer maps, memory bitmaps, defect and FA images, and layout patterns.
Model domain knowledge as graphs and apply GNNs to reveal relationships and suggest root causes.
Integrate AI solutions into high-volume production diagnostics and analytic workflows.
Establish reliable data and retrieval foundations with pipelines, versioning, and grounded retrieval.
Drive adoption across package assembly, silicon yield, diagnostics, and FA by converting manual analyses into automation.
Provide guidance and mentorship to junior engineers as we evolve to an AI-first team.
优先资格
Master’s or PhD in CS, ML/AI, or related field, or equivalent practical experience.
+ years building ML/AI systems, including at least 3 years in the field of electronics or semiconductor manufacturing.
Strong Python and SQL, plus experience with distributed data processing, feature engineering, and model serving at scale.
Hands-on experience with agent frameworks and orchestration of multi-tool chains for automated decision making.
Track record shipping automation that replaced routine analysis or materially reduced analysis time.
Experience with at least two of the following: deep learning, knowledge graphs or GNNs, computer vision, multimodal models, retrieval and grounding, fine-tuning.
AI 洞察
优缺点分析
优点
- Work on cutting-edge AI applications in semiconductor manufacturing, solving real-world problems.
- Join a world-class R&D team at a leading technology company with strong benefits and stability.
- High impact: your work directly improves yield and efficiency of flagship AI chips.
- Requires deep domain knowledge in both AI and semiconductor manufacturing, steep learning curve.
- Onsite commitment (5 days/week) limits remote flexibility.
- Fast-paced environment demanding robust production-grade solutions.
- Experienced AI/ML engineers with a passion for applied research in hardware-related domains, comfortable with complex systems and production deployment.
缺点 / 挑战
暂无明显挑战项
角色解读
- Progress to principal engineer or architect level within Qualcomm's technical ladder.
- Move into AI research or advanced technology development roles in semiconductor or broader tech industry.
- Transition to product leadership or cross-functional AI strategy positions.
- Architect and deploy AI solutions for yield analysis and diagnostics, including GenAI assistants and autonomous agents.
- Develop ML and computer vision models to interpret wafer maps, memory bitmaps, defect images, and layout patterns.
- Model domain knowledge as knowledge graphs and apply GNNs for root cause analysis, integrating insights into production workflows.
- Strong Python, SQL, and experience with distributed data processing and model serving at scale.
- Hands-on experience with agent frameworks, LLM orchestration, and RAG in production.
- Deep understanding of machine learning, deep learning, computer vision, or knowledge graphs/GNNs.
申请策略
- Tailor your resume to reflect both AI and semiconductor experience
- quantify impact of past automation projects.
- Prepare to discuss how you would design an AI solution for a yield problem using the technologies mentioned.
- Emphasize experience building and deploying production AI systems, especially with agentic frameworks and RAG.
- Highlight domain expertise in semiconductor yield, diagnostics, or related fields (e.g., wafer maps, ATPG).
- Showcase track record of automating analytical workflows and reducing manual effort.
- Strengthen knowledge of knowledge graphs, GNNs, and computer vision if not already proficient.
- Gain hands-on experience with LLM orchestration (function calling, tool use) and MLOps.
面试指南
- Use STAR (Situation, Task, Action, Result) to structure answers about past projects
- emphasize quantifiable outcomes.
- For design questions, outline a high-level architecture: data sources, model selection, integration points, and monitoring.
- Show systematic thinking: consider data quality, scalability, reliability, and stakeholder adoption.
- Describe an AI system you deployed that replaced manual analysis. What was the architecture and impact?
- How would you use knowledge graphs and GNNs to diagnose yield issues from wafer map data?
- Explain your approach to building a RAG system for a semiconductor diagnostics runbook.
- What challenges have you faced in integrating ML models into production workflows? How did you address them?
职位点评
69
综合评分
High-impact senior AI role at top semiconductor firm, pioneering AI in yield diagnostics, with strong development prospects but onsite-only requirement.
更适合这类人
This role is ideal for a technically ambitious engineer who prioritizes cutting-edge work and career growth over flexible work arrangements.
表现最好
成长发展
相对薄弱
工作生活
薪资福利70
成长发展85
工作生活40
使命价值80
薪资福利
70中等
High base salary expected for senior role at a top semiconductor company, but salary not explicitly stated in JD; benefits likely excellent but also unstated.
薪资信号未披露（AI估算：40K-60K/月）
成长发展
85较高
Position involves cutting-edge AI technologies (Agentic AI, GNNs, CV) and direct impact on critical chips; mentorship opportunity available; strong growth potential.
技术前沿前沿/新兴技术
技术栈Agentic AI、Knowledge Graphs、GNNs、Computer Vision、LLM、RAG、MLOps、Deep Learning
成长机会Provide guidance and mentorship
业务类型profit_center
工作生活
40较低
Onsite 5 days/week in Hsinchu science park; no mentions of flexible hours or remote work; work-life balance likely typical for semiconductor industry.
工作模式仅现场办公
办公地点科技园/产业园
加班情况未提及（无法判断）
使命价值
80较高
Role contributes to advanced chip yield, impacting many industries; mission statement about 'smarter connected future' adds purpose; semiconductor industry is high-growth.
行业发展高速增长赛道
社会影响中性/一般
使命信号create a smarter, connected future for all
创新程度开拓性创新（行业首创）
Watch Jobs