GPU/AI Application Platform Architect - San Jose

Responsibilities

Server platform team is responsible for architecting, designing and building best server and storage system to meet the requirements of high-performance, low cost and easy to operate. By joining this team, you will work with the best engineers and talents in this industry and have a broad opportunity to get in touch with the latest AI application system and newly emerged technology in computing, storage and silicon validation. You will gain remarkable hardware architect, development and validation experiences in most advanced hardware infrastructure at massive scale.

We are looking for a self-motivated GPU/AI Application Platform Architect with the following responsibilities:
- Track GPU/AI LLM technology from industry and partner vendors. Evaluate and test the new part or technology, integrate the technology into the system.
- Drive GPU/AI LLM platform customization via application performance optimizations and architecture explorations to increase system Perf/TCO and/or reduce system TCO.
- Drive GPU/AI LLM new technology solution study and implementation.
- Evaluate GPU system performance under state-of-art LLM applications.
- Work with industry consortiums and open standard committees to investigate the emerging technologies or standards, and contribute our research results and visions to the industry.
- Work with our technology partners and suppliers to setup POC or prototypes to evaluate and test the new technologies or architectural designs.
- International travel requirement: up to four times per year, including but not limited to China, Europe, and South Asia. Candidates must have a valid passport and be able to obtain the necessary visas.

Qualifications

Minimum Qualifications
- Master's degree or higher in Electrical Engineering, Computer Engineering, Computer Science or related majors.
- Deep understanding of computer system architecture, especially on GPU/AI SoC or Platform Architecture, Interconnect Fabric, and Memory sub-system.
- Experienced in GPU/AI system application performance optimization or software hardware co-design.
- Understand LLM model architecture, familiar with training and inference requirements on accelerator/memory/network.
- Understand the implementation of GPU/AI virtualization technology, deep learning architecture, and distributed system.

Preferred Qualifications
- 3 years experience in GPU/AI LLM platform architecture and/or application performance optimization design or software hardware co-design.
- Demonstrated experience in working collaboratively with cross-functional teams.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $387600 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.

Responsibilities

Responsibilities

Server platform team is responsible for architecting, designing and building best server and storage system to meet the requirements of high-performance, low cost and easy to operate. By joining this team, you will work with the best engineers and talents in this industry and have a broad opportunity to get in touch with the latest AI application system and newly emerged technology in computing, storage and silicon validation. You will gain remarkable hardware architect, development and validation experiences in most advanced hardware infrastructure at massive scale.

We are looking for a self-motivated GPU/AI Application Platform Architect with the following responsibilities:
- Track GPU/AI LLM technology from industry and partner vendors. Evaluate and test the new part or technology, integrate the technology into the system.
- Drive GPU/AI LLM platform customization via application performance optimizations and architecture explorations to increase system Perf/TCO and/or reduce system TCO.
- Drive GPU/AI LLM new technology solution study and implementation.
- Evaluate GPU system performance under state-of-art LLM applications.
- Work with industry consortiums and open standard committees to investigate the emerging technologies or standards, and contribute our research results and visions to the industry.
- Work with our technology partners and suppliers to setup POC or prototypes to evaluate and test the new technologies or architectural designs.
- International travel requirement: up to four times per year, including but not limited to China, Europe, and South Asia. Candidates must have a valid passport and be able to obtain the necessary visas.

Qualifications

Qualifications

Minimum Qualifications
- Master's degree or higher in Electrical Engineering, Computer Engineering, Computer Science or related majors.
- Deep understanding of computer system architecture, especially on GPU/AI SoC or Platform Architecture, Interconnect Fabric, and Memory sub-system.
- Experienced in GPU/AI system application performance optimization or software hardware co-design.
- Understand LLM model architecture, familiar with training and inference requirements on accelerator/memory/network.
- Understand the implementation of GPU/AI virtualization technology, deep learning architecture, and distributed system.

Preferred Qualifications
- 3 years experience in GPU/AI LLM platform architecture and/or application performance optimization design or software hardware co-design.
- Demonstrated experience in working collaboratively with cross-functional teams.