Machine Learning Algorithm/SW Optimization Engineer

• Understand and optimize performance of deep learning libraries through deep knowledge of AI frameworks, algorithms, models, and related hardware.
• You will be responsible for setting up AI workloads, analyze and develop optimization techniques for existing and future compute architecture in collaboration with different stakeholders.
• Explore new algorithms/optimizations for custom achitectures to enable SW-HW codesign.
• You will stay up-to-date with the latest deep learning literature to implement state-of-the-art algorithms.
• You follow up on progress within research projects and are able to communicate the accomplished / in-process work to internal and external stakeholders and adapt where needed.
• During the first few years of your time with AI Models, you will have the opportunity to be an integral part of our ongoing EuroHPC DARE project that aims to drive Europe's independence in high-performance computing and AI.

What we do for you

We offer you the opportunity to join one of the world's premier research centers in nanotechnology at its headquarters in Leuven, Belgium. With your talent, passion and expertise, you'll become part of a team that makes the impossible possible. Together, we shape the technology that will determine the society of tomorrow.

We are committed to being an inclusive employer and proud of our open, multicultural, and informal working environment with ample possibilities to take initiative and show responsibility. We commit to supporting and guiding you in this process; not only with words but also with tangible actions. Through imec.academy, 'our corporate university', we actively invest in your development to further your technical and personal growth.

We are aware that your valuable contribution makes imec a top player in its field. Your energy and commitment are therefore appreciated by means of a market appropriate salary with many fringe benefits.

• You have a PhD, preferable in Computer Science, Engineering, Mathematics, or equivalent.
• Strong background with parallel programming and proven ability of CUDA and Python programming.
• You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax).
• Experience with distributed training frameworks (e.g., Ray, Dask, PyTorch Lightning).
• Strong background in algorithmic optimization techniques like quantization, pruning, and distributed training methodologies.
• Experience in software performance analysis and optimization.
• Prior experience with optimizing AI for AI Compute Architectures is a plus.
• Understanding of performance analysis tools, and hardware optimization techniques.
• You are a team player and have strong communication skills.
• Your English is fluent, both speaking and writing.