Stage ingénieur : Ingénierie produit & IA (F/H)

NXP Semiconductors is seeking a final-year engineering student for a six‑month, on‑site internship in Valbonne, France, to join the Stage ingénieur : Ingénierie produit & IA (F/H) role. The company’s Connectivity and Security business line builds advanced ICs for smartphones, connected devices and smartwatches, with teams around the world working on technologies like NFC and UWB. This opportunity is a fit for someone who wants to combine hands-on engineering with data work and AI in a semiconductor setting.

The internship blends concrete Product Engineering tasks with the digitalization and automation of qualification planning. The goal is to turn a breadth of technical and project data, ranging from qualification tests to sample needs, lab activities, costs and schedules, into practical project insights. You’ll retrieve and structure data from existing web applications, leverage APIs, and develop a reusable framework to generate cost estimates, scheduling forecasts, and dashboards that track progress. Artificial intelligence will play a key role in organizing technical inputs, spotting data gaps or inconsistencies, and producing concise project summaries, all under the validation of engineers.

You’ll work closely with Product Engineers, Qualification Leads and Reliability Engineers to understand how qualification strategies are defined and executed, and you’ll help translate complex technical inputs into user‑oriented digital solutions. The role is a bridge between engineering and data, giving you a chance to see how a semiconductor qualification program is planned and tracked in a real environment.

Day-to-day work in Valbonne

In practice, you’ll collaborate with the product and reliability teams to map how qualification requirements and project data are captured in internal web tools, and you’ll use application interfaces and APIs to gather, exchange and structure this information. You’ll turn technical details into concrete estimates for activities, dependencies, resources, sample needs, equipment, costs and timelines, then build a reusable framework that generates preliminary cost and schedule estimates and keeps qualification progress visible. AI techniques will be used to tidy up technical information, support estimation work, flag data inconsistencies and produce engineering summaries, all while engineers review and validate the outputs. You’ll also contribute to data analysis and follow-up activities tied to the qualification process as needs arise across projects.

Your core requirements

• You're in your final year of an engineering program or pursuing a Master’s in electronics, microelectronics, computer science, data engineering or a related field.

• You’re drawn to semiconductors, qualification, reliability and project management.

• You have an interest in Artificial Intelligence, including generative and agentic AI, and you see practical uses for these in engineering workflows.

• Some early exposure to development, APIs, Python, data processing, databases, Mendix, Excel or Power BI would be helpful as a starting point.

• You can translate a technical process into a structured, user‑oriented digital solution.

• You’re curious, precise and capable of working autonomously.

• English is essential, since most technical conversations and working documents occur in an international setting.

Nice-to-haves

• Any initial experience with building data workflows, API interactions, Python coding or data visualization tools adds value.

• Background with Mendix or similar low‑code platforms can help you prototype solutions more quickly.

• Familiarity with how qualification strategies are defined and executed in real projects would be a plus.

Pay, benefits and practical details

This opportunity is a six‑month, on‑site internship located in Valbonne, France. The description notes English as the working language in an international environment, and the role centers on hands‑on Product Engineering activities alongside data digitization and AI‑driven support for qualification planning.

Getting ready for the interview

Put your most relevant experiences up front, especially any projects where you handled data, APIs, Python or BI tools, and where you helped translate technical requirements into usable outputs. Be prepared to describe a time you turned a complex process into a digital solution and how you collaborated with engineers to validate results.

When you talk about your skills, give concrete examples of how you’ve used data to drive decisions, including any dashboards or estimates you produced. If you’ve worked on AI or data‑driven tools, highlight the problem you tackled, the approach you took and the outcome, with an explicit note on how the work was reviewed or validated by others.

In the interview, expect questions about qualification strategies, data collection in apps, and how you would design a reusable framework to estimate costs, dependencies and schedules. A smart question to end with could be about how AI is applied to organize technical information and support estimation in ongoing qualification programs, and how engineers validate the outputs before they’re used in planning.

More information about NXP in France is available at the linked page: More information about NXP in France...