Machine Learning Engineer Automotive (Customer Facing) (f/m/div)

#WeAreIn for jobs that impact everyone's life. What if your ideas could change the way the world connects, powers up, or thinks? As a Machine Learning Engineer Automotive in our Research & Development team, you'll have the opportunity to merge creativity with your technical expertise by shaping the future of technology, driving groundbreaking projects, and bringing new ideas to life. Are you in? Your role Key responsibilities in your new role At Imagimob, part of Infineon Technologies, you will play a key role in bringing Edge AI to next-generation automotive systems. Working across machine learning, embedded software, and customer applications, you will develop production-ready AI solutions that enable smarter, safer, and more efficient vehicles. • Design, train, validate, and optimize machine learning models for automotive applications on Infineon microcontrollers such as AURIX™, Traveo™ and PSOC™ • Work with sensor, system, and application experts to identify suitable AI approaches for customer problems • Collect, analyze, and preprocess automotive sensor and system data, define data collection and labeling strategies, and develop validation methodologies that ensure robust machine learning model performance under real-world operating conditions • Support customers and internal teams in identifying and evaluating AI use cases and develop proof-of-concepts, demonstrations, and customer reference implementations demonstrating the value of Edge AI in automotive systems • Participate in customer workshops, technical presentations, and solution reviews Your profile Qualifications and skills to help you succeed You are a proactive and collaborative engineer who takes ownership, adapts to evolving priorities, and consistently delivers high-quality solutions. You enjoy working closely with colleagues and customers to drive successful outcomes. • Bachelor’s, Master's, or PhD degree in Computer Science, Machine Learning, Electrical Engineering, Embedded Systems, Artificial Intelligence, or a related technical discipline • Strong understanding of machine learning fundamentals, including supervised and unsupervised learning, time-series analysis, signal processing, and deep learning, with hands-on experience in TensorFlow, PyTorch, Scikit-learn, ONNX, or equivalent frameworks • Experience deploying machine learning models on resource-constrained devices including knowledge of TinyML, model optimization (quantization, compression), feature engineering, and real-time inference • Strong programming skills in C, C++, and Python, with familiarity with RTOS concepts, performance profiling, and automotive-grade microcontrollers • Understanding of automotive electronics, software architectures, and development processes, including familiarity with AUTOSAR and ISO 26262 would be an advantage • Experience in software integration for safety-critical or real-time systems, with exposure to automotive radar, inertial/acoustic sensing, motor control, battery management systems, and industrial sensing applications would be an advantage • Fluency in English Please send us your CV in English. #WeAreIn for driving decarbonization and digitalization. As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener. Are you in? We are on a journey to create the best Infineon for everyone. We strive to create the best Infineon for everyone by embracing diversity and inclusion. We welcome applicants for who they are and offer a workplace built on trust, openness, respect and equal opportunity. Our hiring decisions are based on skills and experience. Even if you don’t meet every requirement, we encourage you to apply. Please let your recruiter know if you need any accommodations during the interview process. Learn more about our various contact channels and about Diversity & Inclusion at Infineon. Luis Oliveira, https://www.linkedin.com/in/luis-oliveiraa/