Photonics AI & Automation Product Engineer

Nokia; Sunnyvale (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Nokia in Sunnyvale, California seeks a Photonic Product Engineer for AI & Automation to drive AI initiatives across PIC, ASIC, TROSA, and Plug, collaborating with Development, Test, Reliability, Quality, Manufacturing, and IT to build reusable tools and data-driven processes.

You will transform engineering data and workflows into AI-ready systems, delivering measurable business impact and embedding AI and automation into everyday engineering practice.

Qualifications

• PhD in engineering or related field required.
• Experience applying AI, analytics, or automation to engineering challenges.
• Strong programming and data analysis skills (Python or similar).
• Experience with AI technologies and data systems for engineering workflows.
• Desirable familiarity with optical transceivers, photonics, DSP, or semiconductor tech.

Responsibilities

• Execute AI and automation initiatives across product engineering domains.
• Drive adoption of AI, ML, automation, and data-driven practices.
• Establish reusable methods, tools, and knowledge systems for AI across lifecycle.
• Transform data, workflows, and traceability into AI-ready systems.
• Build, validate, and deploy tools, agents, and analytics for engineering impact.
• Collaborate with Development, Test, Reliability, Quality, Manufacturing, Operations, and IT.

Skills

PhD in engineering

AI & automation in engineering

Python programming

Data analysis & tool development

Photonic DSP/semiconductor tech

Education

PhD in Electrical Engineering/CS/Data Science

Tools

Python

DSP tools

Photonic engineering software

Job description

Nokia in Sunnyvale, California seeks a Photonic Product Engineer for AI & Automation to drive AI initiatives across PIC, ASIC, TROSA, and Plug, collaborating with Development, Test, Reliability, Quality, Manufacturing, and IT to build reusable tools and data-driven processes.

You will transform engineering data and workflows into AI-ready systems, delivering measurable business impact and embedding AI and automation into everyday engineering practice.