Stage ingénieur : Analyse de la consommation et optimisation des tests pour les System-on-Chip (SoC) de nouvelle génération (H/F)

NXP Semiconductors is hiring for an onsite internship in its Advanced Chip Engineering team, based in Sophia Antipolis (Valbonne). The six-month program focuses on analyzing energy consumption and optimizing test strategies for next-generation System-on-Chip devices. This opportunity is aimed at Master’s degree students or engineering school graduates who are excited by semiconductor technology, digital design, data science, automation, and the practical use of AI in engineering.

Located in Valbonne, you’ll join a team that develops state-of-the-art SoC solutions using the latest fabrication technologies, advanced design methodologies, and top-tier EDA tools. As chip complexity grows, the project targets high performance, low power, strong reliability, and high-quality testing, with AI tools gradually shaping how engineers analyze data and make decisions throughout the development cycle.

The internship is designed for highly motivated individuals who want hands-on exposure across several stages of the SoC flow, from Design-for-Test and hardware emulation to silicon data analysis and AI-assisted engineering. You’ll work with industry-grade tools, study real silicon data from cutting-edge components, and contribute to methodologies that better align pre-silicon predictions with post-silicon measurements.

A day-to-day rhythm in the DFT lab

Within the DFT team, you’ll explore the links between how a chip uses power during test, the quality of its tests, and the resulting silicon performance. Your daily work will blend hands-on experimentation with data analysis, using modern methodologies to push a multi-million-gate SoC through its test flow. Expect to engage with advanced simulation and hardware emulation platforms to run, debug, and analyze different DFT test scenarios, translating findings into actionable improvements.

You will study test power consumption and power-aware testing techniques, tracking metrics across the full development path, from physical implementation to silicon characterization. You’ll help assess test coverage, fault models, and yield indicators to gain a clearer picture of product quality, while handling large volumes of data from simulations, emulation, production tests, and post-silicon characterization. The role also invites you to apply AI to uncover patterns, detect anomalies, and sharpen engineering insights, and to develop automation solutions in Python that streamline reporting and boost productivity. Collaboration with seasoned engineers in digital design, DFT, physical implementation, and silicon validation is a constant part of the job, and you’ll present your technical results and recommendations to engineering teams and project stakeholders.

Your profile essentials

You must have these qualifications:

• A Master’s degree in Electronics, Microelectronics, Embedded Systems, or a related field

• Solid knowledge of the circuit design process and basic understanding of digital design and semiconductor technologies

• Experience with Python programming and AI-driven development

• Good English communication skills

• Strong analytical and problem-solving abilities

Nice-to-have:

• Some exposure to DFT concepts or test methodologies beyond the basics, such as scan insertion or test coverage considerations

• Experience with data analytics tools beyond standard coursework, especially in automation or AI-assisted workflows

More information about NXP in France...

Advice for applicants

Put the most relevant credentials up front. In your resume, lead with your Master’s program or engineering school and the field that aligns with this role, then highlight any projects or coursework that touched on digital design, DFT, or data analysis.

Show concrete evidence of the must-have skills. Describe a Python project where you used AI techniques to analyze electrical data, optimize a test flow, or automate a reporting pipeline, and mention any hands-on experience with test methodologies or scan techniques if you have it.

Prepare for interviews with specifics from the role. Be ready to discuss topics like scan insertion, scan compression, ATPG, JTAG, BIST, fault simulation, and test coverage optimization, and connect them to how you would analyze power during testing and interpret metrics from simulations to post-silicon results.

Ask a targeted question to demonstrate strategic thinking. For example: what are the current challenges in bridging pre-silicon predictions with post-silicon measurements, and how is AI being used to enhance the interpretation of silicon data in this team?