We are seeking an experienced Solution Architect with a focus on GPU technology, strong solution design capabilities, and extensive hands-on experience. You will work closely with clients, product managers, and engineers to design and deliver high-performance computing solutions based on GPUs, driving innovation in artificial intelligence, deep learning, graphics rendering, and other fields.

Responsibilities:

• Solution Design: Communicate with clients to deeply understand business needs and technical challenges, and design GPU-based solution architectures, including hardware selection, software stack selection, system integration, and performance optimization.
• Technical Consulting: Provide clients with GPU-related technical consulting services, including GPU architecture, programming models, performance tuning, and deep learning frameworks.
• Prototype Development: Conduct technical feasibility verification, build prototype systems, perform performance testing and optimization, and ensure the feasibility and efficiency of solutions.
• Project Implementation: Participate in project implementation, provide technical guidance and support, solve technical challenges, and ensure timely and high-quality project delivery.
• Technical Research: Stay updated on GPU technology trends, research new technologies and applications, and apply them to real-world projects.
• Documentation: Write technical proposals, design documents, user manuals, and other documentation.

Requirements:

Education: Bachelor's degree or higher.

Experience: 5+ years of relevant work experience with extensive GPU solution design and hands-on experience.

Technical Skills:

• Proficient in GPU architecture and programming models.
• Familiar with mainstream deep learning frameworks.
• Familiar with high-performance computing, parallel computing, and distributed computing technologies.

Abilities:

• Strong solution design and problem-solving skills.
• Excellent communication and teamwork skills.
• Strong learning ability and passion for technical research.

Preferred Qualifications:

• Experience in deploying and managing large-scale GPU clusters.
• Experience with cloud platforms (e.g., AWS, Azure, GCP).
• Experience with container technologies (e.g., Docker, Kubernetes).