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Senior Machine Learning Hardware Architect
On-siteFull-timeHardware EngineeringEnterprise SoftwareData Infrastructure
Lead the architecture and hardware-software co-design of next-generation machine learning accelerators. Define roadmaps, performance models, and system strategies for large-scale training and inference across hardware, software, compiler, and ML teams. The role is based in Israel, with preferred工作地点
Responsibilities
- Define the technical roadmap and architecture for the machine learning hardware-software stack.
- Coordinate model architecture innovation across research, software, and hardware teams.
- Architect configurable simulation frameworks and performance models for microarchitectural decisions.
- Evaluate power, performance, area, buildability, and delivery trade-offs for chip and system architectures.
- Lead system-level performance analysis across distributed ML systems, including compute, memory bandwidth, and inter-chip networking.
- Manage cross-functional partnerships across hardware, compiler development, and ML teams.
Requirements
- Bachelor’s degree in electrical engineering, computer engineering, computer science, a related field, or equivalent practical experience.
- 12 years of experience in computer architecture, chip architecture, or hardware-software co-design.
- Experience developing C++ or Python software for performance modeling, simulation, or system analysis.
Nice to have
- Master’s degree or PhD in electrical engineering, computer engineering, or computer science focused on computer architecture.
- Experience leading multi-generational hardware solutions or performance optimization for large-scale ML training and inference.
- Knowledge of semiconductor technologies, process, memory, interconnect, and packaging trends.
- Experience with TensorFlow, PyTorch, or comparable deep learning frameworks and their execution models.