Expert level expertise in PyTorch and inference focused model optimization; strong Python engineering skills.
Hands on experience with torch.compile / TorchDynamo or related graph capture and compilation workflows.
Deep understanding of transformer architectures, attention mechanisms, MoEs, and performance trade-offs.
Practical experience with KVcache behavior, serving time optimizations, and memory/performance tradeoffs.
Strong foundation in computer architecture, ML accelerators, and distributed systems.
Proven ability to lead cross-functional technical efforts and influence design decisions.
MS in Computer Science, Machine Learning, Computer Engineering, or Electrical Engineering, or equivalent experience.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, or related work experience.