Machine Learning Algorithm/SW Optimization Engineer Join to apply for the Machine Learning Algorithm/SW Optimization Engineer role at imec. What you will do Understand and optimize performance of deep learning libraries through deep knowledge of AI frameworks, algorithms, models, and related hardware. Set up AI workloads, analyze, and develop optimization techniques for existing and future compute architectures in collaboration with stakeholders. Explore new algorithms/optimizations for custom architectures to enable SW-HW co-design. Stay current with deep learning literature to implement state-of-the-art algorithms. Communicate progress within research projects to stakeholders and adapt as needed. Participate in the EuroHPC DARE project to advance Europe's independence in high-performance computing and AI. What we do for you Join a leading research center in nanotechnology at imec's headquarters in Leuven, Belgium. We foster an inclusive, multicultural, and innovative environment with opportunities for personal and professional growth through imec.academy. We offer a competitive salary with fringe benefits, recognizing your valuable contributions. Who You Are PhD in Computer Science, Engineering, Mathematics, or related field. Proficient in parallel programming, CUDA, Python. Experience with Deep Learning Frameworks (PyTorch, TensorFlow, Jax). Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning). Knowledge of optimization techniques like quantization, pruning, distributed training. Experience in software performance analysis and hardware optimization. Experience with AI compute architecture optimization is a plus. Strong communication skills and team-oriented mindset. Fluent in English, both spoken and written. Note: IMEC accepts resumes only directly from candidates or through approved channels. Unsolicited resumes from agencies without prior agreement will not be accepted or compensated. #J-18808-Ljbffr