Machine Learning Researcher

Machine Learning Performance Researcher Job Description

TheAIdepartmentis a department in the ISSA expertise center that develops advanced AI solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid hardware architectures. The application domains are diverse, ranging from AI for science, over AI for semiconductor process technology to automotive and health applications.

Within this department, the Optimized AI team focuses on computing techniques to scale up a wide range of AI approaches and drive the SW‑HW‑Technology co‑optimization. We analyze and implement AI models and software architectures while investigating bottlenecks with the purpose of solving them at algorithmic, implementation and/or hardware level, in close collaboration with imec’s architecture and technology groups.

Join us if you love to deeply understand how various AI algorithms work and how to implement them efficiently on a wide range of existing and upcoming hardware. Help us push the boundaries of AI compute, collaborating with industry leaders, and helping to develop the next generation of AI algorithms & systems.

• You explore new algorithms / optimizations for custom architectures to enable SW‑HW code‑design and help shape our activities around this.
• You understand and optimize performance of various (local and distributed) AI and hybrid AI applications, frameworks, algorithms and libraries.
• You guide and help develop mini‑applications that embody key AI workloads by combining multiple underlying kernels and the key data communications between them.
• You guide and help analysis and optimization of the performance of mini‑applications on both existing hardware and simulated novel hardware and use the outcomes for further hardware/software explorations.
• 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 directions where needed.

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.
• You have a strong background with parallel and distributed programming models and high‑performance computing techniques and machine learning models.
• Practical experience in the programming of high‑performance computing of AI and/or scientific computing applications or libraries.
• Strong background in algorithmic optimisation techniques like quantisation, pruning, and distributed training methodologies.
• You have experience using performance analysis tools, and hardware optimisation techniques.
• You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax) and proven ability of CUDA and Python programming.
• Knowledge of, or prior experience with, optimising AI for AI Compute Architectures is a plus.
• You are a team player and have strong communication skills.
• Your English is fluent, both speaking and writing.

IMEC and its affiliates will not accept unsolicited resumes from any source other than directly from a candidate. IMEC will consider unsolicited referrals and/or resumes submitted by vendors such as search firms, staffing…