Industrial Postdoc - AI Compilers

Your mission

• Win funding for our next big ideas: spot the right national and European calls, build consortia, and coordinate and write grant proposals from first idea to submission
• Lead funded projects from kick-off to final report: track milestones, deliverables and budgets, and act as the main contact for funding agencies and consortium partners
• Turn our R&D results into high-quality papers for leading compiler, systems and ML conferences and journals, working closely with our engineers
• Shape our research agenda where science meets startup, and translate our technical roadmap into compelling research and funding strategies
• Build and grow partnerships with universities, research institutes and industry across Europe
• Represent Roofline in the research community at conferences, workshops and collaborations

Your profile

• PhD in Computer Science, Electrical Engineering or a related field, or an MSc with substantial research experience
• Experience writing and coordinating research grant proposals, ideally at national or European level
• A publication record in compilers, ML systems, HPC, computer architecture or a related area
• Hands-on programming skills in Python or C++, or the ability to build working code with AI tools, to run experiments and get to publishable results
• Enough technical depth to understand our compiler technology and turn it into convincing proposals and papers
• Excellent written English and the ability to explain complex technical work to different audiences, from reviewers to customers
• Strong organizational skills and the ability to juggle several proposals, projects and deadlines at once
• An entrepreneurial mindset: you see opportunities, take ownership, and want to build something rather than just study it

Nice to haves:

• A track record of successful grant applications, or experience managing funded projects (e.g., Horizon Europe, EIC, BMFTR)
• An existing network in the European research community
• German language skills (helpful for national funding programs)
• Experience leading or coordinating research consortia
• Familiarity with MLIR or LLVM, AI accelerators, or hardware architectures for CPUs, GPUs or NPUs
• Experience benchmarking or profiling AI models on embedded hardware or SoCs

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Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation