About the Role
We are seeking an experienced Software Engineer for Automotive AI Inference to develop and optimize the software stack that enables machine learning inference on Infineon Automotive microcontrollers.
In this role, you will work at the intersection of machine learning, compiler technologies, embedded software, runtime optimization, and automotive systems. You will be responsible for building the foundational software components that allow ML models to be deployed efficiently on automotive-grade MCUs while meeting stringent requirements for performance, memory utilization, reliability, and functional safety.
You will collaborate closely with MCU architects, automotive application teams, and strategic customers to deliver production-ready AI software solutions for next-generation vehicles.
Key Responsibilities
- Design and implement high-performance inference runtimes for Infineon Automotive microcontrollers and integrate AI inference pipelines into embedded software stacks and real-time operating system environments.
- Optimize models and runtime performance for latency, memory usage, power efficiency, and reliability.
- Utilize MCU-specific acceleration capabilities and architecture-specific optimizations and implement highly efficient mathematical libraries for embedded inference.
- Work closely with cross-functional teams including firmware, hardware, and algorithm engineers to ensure successful system integration.
- Support maintainable deployment processes through version control, reproducibility, and traceability.
- Evaluate and apply appropriate tools and frameworks for model conversion, quantization, and on-device inference.
- Support strategic automotive customers during proof-of-concept and production phases and provide technical guidance on AI deployment best practices.
Required Qualifications
- Bachelor's or Master's degree in: Computer Science, Electrical Engineering, Embedded Systems, Computer Engineering, Software Engineering or a related technical field
- Good understanding of model quantization, memory optimization and performance tuning on constrained hardware.
- Experience deploying AI/ML models to edge devices using frameworks or toolchains such as TensorFlow Lite Micro, ONNX, ExecuTorch, or similar
- Familiarity with sensor or signal processing workflows, including time-series data such as vibration, audio, current, or power signals.
- Strong debugging and problem-solving skills across software, model, and hardware integration layers.
- Ability to support the full deployment lifecycle from prototype through production.
- Proactive self-starter who takes ownership, contributes to strategic discussions, adapts to evolving priorities, and helps shape the future of our products.
- Collaborative and independent engineer who maintains high programming standards while supporting colleagues and ensuring customer success.
Preferred Qualifications
- Experience in Automotive embedded applications, incl. experience with / exposure to ISO 26262 and AUTOSAR requirements.
- Experience with MCU-based AI acceleration or related edge inference platforms.
- Knowledge of model lifecycle management, firmware release processes, and production validation.
- Experience using Python-based ML tools for model preparation, evaluation, and conversion
What we offer:
- The opportunity to further develop our development platform, responsible for bringing deep learning to the edge
- Being a part of an excellent international team with highly motivated individuals striving for a common goal
- A chance to be a part of solving real-world problems using ML
- Competitive salary, wellness allowance, possibility to attend online-courses
- A humble and an open-minded company culture
- Opportunities to grow with the company and advance your career
- Short decision paths, we love getting things done
- An office in central Stockholm and the flexibility of working from home