Accelerator Architect and Performance Engineer, Generative AI

AECOM; Mountain View (CA); On-site; USD 183,000 - 271,000; Full time

Job summary

AECOM seeks a skilled Generative AI Architect to lead innovative projects in AI model architectures. You will drive exploration for advanced machine learning frameworks, collaborating across teams to refine system architecture for optimized performance. Ideal candidates will possess a strong background in Electrical Engineering or related fields, with demonstrated expertise in programming and excellent communication skills. This role offers a competitive salary and a chance to shape the future of technology at a leading firm.

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Science or equivalent plus 8 years experience.
• Experience with Generative AI model architectures and programming languages.
• Excellent communication skills plus advanced architectural research applied to GenAI workloads.

Responsibilities

• Drive exploration of GenAI architecture for mobile SoCs and optimize workloads.
• Collaborate with research and programs to define architectural requirements.
• Enhance performance of Generative AI use cases on TPU compute engines.

Skills

Generative AI model architectures

C/C++

Python

deep learning frameworks

hardware/software co-design

distributed programming

communication skills

Education

Bachelor's degree in Electrical Engineering

Master's degree or PhD in related fields

Tools

TensorFlow

Jax

Pytorch

Job description

Minimum qualifications:

+ Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.

+ 8 years of work or academic research experience in computer or chip architecture, performance, or compiler.

+ Experience with Generative AI model architectures (e.g., Large Language Models, Vision Transformers, Image Diffusion Models, etc.).

+ Experience with one or more general purpose programming languages including (but not limited to) C/C++ or Python and deep learning frameworks like TensorFlow/Jax/Pytorch.

Preferred qualifications:

+ Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.

+ Experience with domain-specific accelerators.

+ Experience with distributed/parallel programming.

+ Experience with hardware/software co-design for machine learning.

+ Experience with simulator development and micro-architecture.

+ Excellent communication skills.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

The US base salary range for this full-time position is $183,000-$271,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google (https://careers.google.com/benefits/) .

+ Drive forward-looking GenAI machine learning architecture exploration for Tensor mobile SoCs while collaborating with research teams, system architecture teams, and compiler engineers to optimize future workloads from both all perspectives across the tech stack including hardware, software, use case, network, and external components.

+ Work with researchers and program management teams to define system architecture requirements for future Generative AI use cases.

+ Apply advanced research in architecture and process technology to get breakthrough power and performance improvements on Generative AI workloads.

+ Optimize performance of GenAI use cases by defining an optimal model scheduling on the TPU compute engines.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.