Silicon Architecture/Design Engineer, PhD, Early Career
Description For Silicon Architecture/Design Engineer, PhD, Early Career
Join Google's ML, Systems, & Cloud AI (MSCA) organization as a Silicon Architect/Design Engineer, where you'll shape the future of AI/ML hardware acceleration through cutting-edge TPU (Tensor Processing Unit) technology. This role combines hardware architecture, machine learning, and system design to drive Google's most demanding AI/ML applications. You'll work at the intersection of hardware and software, collaborating with multiple teams to optimize performance, power efficiency, and feature implementation.
The position requires expertise in accelerator architectures, programming languages, and hardware design tools. You'll be responsible for developing next-generation TPU architectures, conducting performance analysis, and implementing hardware/software interfaces. The role involves working with Google's global infrastructure that powers services like Search, YouTube, and Google Cloud.
As part of the MSCA organization, you'll contribute to the infrastructure that supports billions of users worldwide. The team prioritizes security, efficiency, and reliability while pushing the boundaries of hyperscale computing. This is an opportunity to work on projects with global impact, including Google Cloud's Vertex AI platform and enterprise-level Gemini models.
The ideal candidate should have a PhD in a relevant field and experience with hardware design and ML systems. You'll be part of a team that values innovation, collaboration, and technical excellence, working in an environment that supports professional growth and impactful contributions to the future of AI hardware.
Responsibilities For Silicon Architecture/Design Engineer, PhD, Early Career
- Revolutionize Machine Learning (ML) workload characterization and benchmarking, and propose capabilities and optimizations for next-generation TPUs
- Develop architecture specifications that meet current and future computing requirements for AI/ML roadmap
- Partner with hardware design, software, compiler, Machine Learning (ML) model and research teams for effective hardware/software codesign
- Develop and adopt advanced AI/ML capabilities, drive accelerated and efficient design verification strategies
- Use AI techniques for faster and optimal Physical Design Convergence
Requirements For Silicon Architecture/Design Engineer, PhD, Early Career
- PhD degree in Electronics and Communication Engineering, Electrical Engineering, Computer Engineering or related technical field, or equivalent practical experience
- Experience with accelerator architectures and data center workloads
- Experience in programming languages (e.g., C++, Python, Verilog), Synopsys, Cadence tools
- 2 years of experience post PhD (preferred)
- Experience with performance modeling tools (preferred)
- Knowledge of arithmetic units, bus architectures, accelerators, or memory hierarchies (preferred)
- Knowledge of high performance and low power design techniques (preferred)
Benefits For Silicon Architecture/Design Engineer, PhD, Early Career
- Comprehensive health benefits
- Parental leave
- Equal employment opportunity
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