3 months ago
Responsibilities
- Execute Product Engineering AI and automation initiatives across PIC, ASIC, TROSA, and Plug.
- Drive adoption of AI, machine learning, automation, and data-driven engineering practices.
- Establish common methods, frameworks, and knowledge systems for scalable AI use across the product lifecycle.
- Transform engineering data, workflows, and traceability into AI-ready systems spanning development, qualification, manufacturing, reliability, and field performance.
- Build, validate, and deploy reusable tools, agents, analytics, and automation solutions.
- Partner with Development, Test, Reliability, Quality, Manufacturing, Operations, and IT teams to align data, tools, and practices.
Requirements
- PhD in Electrical Engineering, Computer Science, Data Science, Physics, Photonics, Applied Mathematics, or a related field.
- Experience applying AI, machine learning, analytics, software, or automation to engineering, product development, test, or manufacturing challenges.
- Strong programming, data analysis, and tool development skills using Python or similar technologies.
- Experience with AI technologies, engineering data systems, knowledge management, traceability, or decision-support tools.
- Experience with optical transceiver products, photonics, DSP, semiconductor technologies, Product Engineering processes, or manufacturing and test systems is highly desirable.
Benefits
- The position is based in Sunnyvale, California.
Tech Stack
Categories
AI ApplicationsProduct Engineering
About Nokia
Nokia builds telecom network equipment and software—covering mobile (4G/5G RAN and core), IP and optical networking, fixed access, and related services—for communications service providers, enterprises, and governments. The company also conducts advanced research through Nokia Bell Labs. Founded in 1865 and headquartered in Espoo, Finland, Nokia is a public company with global operations and long-standing relationships with major mobile network operators worldwide.