Renesas Electronics Sr. Staff Embedded AI Engineer \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . Sr. Staff Embedded AI Engineer Full-time Employment Type: Regular (PERM) Remote Work Available: No Company Description Renesas is seeking a Sr. Staff Embedded AI Engineer to develop advanced TinyML and embedded AI solutions targeting Renesas microcontroller and MPU platforms (RA, RL78, RX, RZ). This is a highly technical, hands-on role focused on building cloud-based model translation infrastructure and optimizing network inference for resource-constrained embedded systems. You will contribute to a small team developing a service that converts trained machine learning models into efficient C/C++ implementations for deployment on microcontrollers. The ideal candidate combines strong embedded software expertise with solid machine learning fundamentals and is comfortable working across the stack from neural network internals to low-level performance optimization. You should be someone who contributes new ideas, challenges assumptions, and helps improve both tooling and embedded implementation quality Job Description BS/MS/PhD in Electrical Engineering, Computer Engineering, Computer Science, or related field. 6+ years of experience in embedded systems software development. Strong proficiency in C/C++ for embedded platforms. Strong proficiency in Python for tooling, automation, or ML workflows. Experience deploying machine learning models to resource-constrained systems. Solid understanding of neural network fundamentals and internals Experience with machine learning frameworks such as TensorFlow or PyTorch. Experience optimizing performance, memory footprint, and power consumption on embedded targets. Qualifications Experience developing inference runtimes, model translation tools, or code generation systems. Experience with CMSIS-NN or other embedded ML acceleration libraries. Experience optimizing quantized neural networks for embedded systems using SIMD/DSP acceleration. Familiarity with Renesas MCU/MPU platforms (RA, RL78, RX, RZ). Experience with real-time systems (RTOS or bare-metal). Hardware debugging experience. Additional Information Renesas is an embedded semiconductor solution provider driven by its Purpose To Make Our Lives Easier. As the industrys leading expert in embedded processing with unmatched quality and system-level know-how, we have evolved to provide scalable and comprehensive semiconductor solutions for automotive, industrial, infrastructure, and IoT industries based on the broadest product portfolio, including High Performance Computing, Embedded Processing, Analog & Connectivity, and Power. With a diverse team of over 22,000 professionals in more than 30 countries, we continue to expand our boundaries to offer enhanced user experiences through digitalization and usher into a new era of innovation. We design and develop sustainable, power-efficient solutions today that help people and communities thrive tomorrow, To Make Our Lives Easier. At Renesas, you can: Launch and advance your career in technical and business roles across four Product Groups and various corporate functions. You will have the opportunities to explore our hardware and software capabilities and try new things. Make a real impact by developing innovative products and solutions to meet our global customers' evolving needs and help make peoples lives easier, safe and secure. Maximize your performance and wellbeing in our flexible and inclusive work environment. Our people-first culture and global support system, including the remote work option and Employee Resource Groups, will help you excel from the first day. Are you ready to own your success and make your mark? Join Renesas. Shape Your Future with Us. Renesas Electronics is an equal opportunity and affirmative action employer, committed to celebrating diversity and fostering a work environment free of discrimination on the basis of sex, race, religion, national origin, gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, or any other basis protected by federal, state or local law. For more information, please read our Diversity & Inclusion Statement. Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas. We have adopted a hybrid model that gives employees the ability to work remotely two days a week while ensuring that we come together as a team in the office the rest of the time. The designated in-office days are Tuesday through Thursday for innovation, collaboration and continuous learning. Videos To Watch I'm interested I'm interestedPrivacy NoticeCookies Settings I'm interested Refer a friend share this job Share on LinkedIn Share on Facebook Share on Twitter Share via email Share on Xing Share on WeChat Other jobs at Renesas Electronics Staff Validation Engineer Tempe, Arizona Staff Package Design Engineer Taipei, Taiwan Sr Staff Package Design and Develop Engineer (Power package)) Ipoh, Malaysia Show all jobs Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share. × Continue Sr. Staff Embedded AI Engineer Columbia, MARYLAND Full-time I'm interested I'm interested

The role requires a BS/MS/PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Candidates must have at least 6 years of experience in embedded systems software development. Strong proficiency in C/C++ for embedded platforms and Python for tooling, automation, or ML workflows is essential. Experience deploying machine learning models to resource-constrained systems and a solid understanding of neural network fundamentals are necessary. Experience with machine learning frameworks such as TensorFlow or PyTorch is also required.