System on Chip Architect
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Snapshot
At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. We are seeking a highly motivated SoC Architect to join our team and contribute to the development of groundbreaking silicon for machine learning acceleration.
About us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
About you
We seek out individuals who thrive in ambiguity and who are willing to help out with whatever moves silicon design and architecture forward. We regularly need to invent novel solutions to problems, and often change course if our ideas don’t work out, so flexibility and adaptability to work on any project is a must.
The Role
We are seeking a talented and highly motivated SoC Architect to join our GenAI technical infrastructure research hardware team. You will be responsible for defining the top-level SoC architecture and chiplet strategy for our next-generation ML accelerators. This role requires deep expertise in SoC design, chiplet integration, and ML-specific hardware.
Responsibilities:
- Define and own the System-on-Chip (SoC) architecture for next-generation ML accelerators.
- Lead the architecture and design of the chip top-level, managing interfaces, clocking, power, and integration of all major IP blocks.
- Architect specific accelerator components and chiplets.
- Collaborate with micro-architecture and physical design teams to ensure a feasible and optimal design, making trade-offs in performance, power, and area (PPA).
- Work with systems and software teams to ensure the SoC architecture meets product requirements.
- Participate in the system architecture definition and evaluation.
Minimum Qualifications:
- Bachelor's degree in Electrical Engineering, Computer Science, or equivalent practical experience.
- 7+ years of experience in SoC architecture or micro-architecture.
- Proven experience in chip top-level design and integration for complex ASICs.
- Hands-on knowledge of hardware building blocks for ML accelerators (matrix multiply units, vector engines, attention mechanisms).
- Experience in evaluating trade-offs such as speed, performance, power, and area.
Preferred Qualifications:
- Master's or Ph.D. in a related field.
- Experience with chiplet-based designs and high-speed die-to-die interconnects (e.g., UCIe, CXL).
- Knowledge of high-performance and low-power architectures for ML acceleration.
- Working knowledge of transformer-based large language models.
- Good understanding of the full ASIC design flow (RTL, verification, synthesis, PD).
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