Senior Architect – Compute Platform

Senior Architect – Future Compute Platform About imec Qatar

Imec Qatar is a new regional office where we drive our mission of pioneering innovative semiconductor solutions that lay the foundation for a smarter, greener, and truly AI-driven future.

Specializing in advanced design tools for emerging technologies like silicon photonics and 3D integrated circuits, imec Qatar is at the forefront of chip development. Andwe'redriving the future with intelligent solutions tooptimizeinfrastructure, and deep-tech innovations targeting applications for a sustainable society.
This is more than just a new office
-it'sthe start of an exciting journey. With the launch of imec Qatar, you have the unique opportunity to join us from day one and help shape the future of semiconductor innovation in the region. Be part of the team from the very beginning, joining us asSenior

Architect – Future Compute Platform!

Joinimec'sFalcon Research Center in Qatar as a Senior Researcher at the intersection of artificial intelligence and computer architecture. You will pioneer the application of advanced AI techniques to revolutionize how we design andoptimizefuture compute platforms, working oncutting-edge

RISC-V based architectures for HPC and Mobile SoC applications.
In this highly collaborative role, you'llbridge the worlds of machine learning and chip design, developing AI-assisted tools and methodologies that accelerate architecture exploration,optimizedesign decisions, andvalidateperformance. Working alongside computer architects, chip designers, and software engineers,you'lltranslate research innovations into practical tools and frameworks that push the boundaries ofwhat'spossible in compute platform design.

• Research & Technical Leadership
  • Lead research initiatives applying AI/ML to computer architecture design space exploration
  • Develop and implement AI-assisted methodologies for architecture optimization, performance prediction, and design validation
  • Define technical direction for projects in collaboration with Compute Research and AI leadership
  • Guide the team in achieving key milestones of the Compute Research roadmap
• Hands-On Development & Implementation
  • Design and implement AI models for architecture performance prediction, workload characterization, and design space exploration
  • Develop surrogate models and optimization frameworks for rapid architecture evaluation
  • Build tools and frameworks enabling heterogeneous compute platform design and validation
  • Contribute to the reference architecture implementation, integrating AI-assisted design flows
  • Take proof-of-concepts through to working prototypes and demonstration systems
• Collaboration & Mentorship
  • Work in a multidisciplinary team spanning ML researchers, computer architects, and chip designers
  • Provide technical guidance and mentorship to team members on AI/ML methodologies
  • Foster knowledge exchange between AI and hardware design domains
  • Lead by example through hands-on contributions and collaborative problem-solving
• Scientific Contribution
  • Publish research findings in top-tier ML and computer architecture venues
  • Present work at international conferences and technical workshops
  • Contribute to open-source tools and frameworks in the AI-assisted design community
  • Stay current with state-of-the-art in both AI/ML and computer architecture research

You will join a world-class research center in nanotechnology at our brand-new office in Doha (Qatar). You will build a team that shapes technology that willdeterminethe society of tomorrow.

Imec is an inclusive employer with an open, multicultural, and informal working environment. We provide ample room for initiative and professional development.

Required skills

• PhD in Computer Science, Electrical Engineering, Machine Learning, or related STEM field (or MSc with 8+ years equivalent experience)
• 5+ years of experience in applied research and/or development of AI/ML applications
• Deepexpertisein one or more of the following:
• Reinforcement Learning for design optimization
• Bayesian Optimization and hyperparameter tuning
• Graph Neural Networks for hardware representation
• Surrogatemodelingand transfer…