What you'll be doing:

• Benchmark and analyze AI workloads in single and multi-node configurations.

• High level simulator and debugger development in C++/Python.

• Evaluate PPA (performance, power, area) for hardware features and system-level architectural trade-offs.

• Work closely with wider architecture teams, architecture and product management to help with trade-off analysis at every stage of the project.

• Keep abreast with emerging trends and research in deep learning.

What we need to see:

• MS or PhD in a relevant discipline (CS, EE, Math).

• 2+ years of experience in parallel computing architectures, interconnect fabrics and deep learning applications.

• Strong programming skills in C, C++ and Python.

• Proficiency in architecture analysis and performance modeling.

• Curious mindset with excellent problem solving skills.

Ways to stand out from the crowd: 

• Understanding of modern transformer-based model architectures.

• Experience with benchmarking, projections methodologies, workload profiling and correlation.

• Ability to simplify and communicate rich technical concepts with non-technical audience.

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