30+ days
36 Amd Jobs - October 2026 - High Salaries
Showing 36 jobs results for
"amd"
- Collaborating with software and hardware engineers to understand system requirements and contribute to performance improvements.
27 days
- Collaborating with software and hardware engineers to understand system requirements and contribute to performance improvements.
29 days
- Collaborating with software and hardware engineers to understand system requirements and contribute to performance improvements.
7 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
27 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
9 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
29 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
29 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
29 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
7 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
7 days
- Participate in offline-to-online synchronization, data consistency, and model-update timeliness optimization and handle traffic scheduling for heterogeneous resources
27 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
27 days
- Design and implement workload scheduling across multiple data centers, regions, and cloud environments, ensuring balanced resource utilization and efficient placement of both online services and offline batch jobs.
27 days
- Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
27 days
- Design and implement workload scheduling across multiple data centers, regions, and cloud environments, ensuring balanced resource utilization and efficient placement of both online services and offline batch jobs.
29 days
- Design and implement workload scheduling across multiple data centers, regions, and cloud environments, ensuring balanced resource utilization and efficient placement of both online services and offline batch jobs.
7 days
- Participate in offline-to-online synchronization, data consistency, and model-update timeliness optimization and handle traffic scheduling for heterogeneous resources
5 days
- Follow up on cutting-edge technologies such as global large model inference, GPU high-performance computing, distributed parallelism, and cache optimization, benchmark against mainstream inference frameworks such as vLLM and TensorRT-LLM, complete the implementation of solutions and technological innovation, continuously iterate and optimize the performance and cost advantages of the inference system, and build the core technological barriers of the team.
27 days
- For inference track, develop the Volcano Ark MaaS (Model-as-a-Service) inference platform, optimizing the performance, cost efficiency, and reliability of large language model inference across hyperscale heterogeneous GPU clusters.
27 days
- Holds a doctoral degree, with preference for candidates majoring in Computer Science, Software Engineering, or related fields.
27 days
- Individuals who are completing or have recently completed a Bachelor's/ Master's degree in computing or a related discipline.
27 days
- Ensure the quality of online services under high-concurrency and large-scale workloads by building robust performance optimization, reliability, and observability capabilities across the Agent platform.
10 days
- For inference track, develop the Volcano Ark MaaS (Model-as-a-Service) inference platform, optimizing the performance, cost efficiency, and reliability of large language model inference across hyperscale heterogeneous GPU clusters.
30+ days
- Collaborate with the business and algorithm teams to identify performance issues, provide full stack performance analysis, bottleneck diagnosis, and optimization solutions, consolidate general-purpose performance optimization components, toolchains, and platform capabilities, and empower multiple internal business.
29 days
- Holds a doctoral degree, with preference for candidates majoring in Computer Science, Software Engineering, or related fields.
29 days
- Individuals who are completing or have recently completed a Bachelor's/ Master's degree in computing or a related discipline.
29 days
- Collaborate with the business and algorithm teams to identify performance issues, provide full stack performance analysis, bottleneck diagnosis, and optimization solutions, consolidate general-purpose performance optimization components, toolchains, and platform capabilities, and empower multiple internal business.
8 days
- Follow up on cutting-edge technologies such as global large model inference, GPU high-performance computing, distributed parallelism, and cache optimization, benchmark against mainstream inference frameworks such as vLLM and TensorRT-LLM, complete the implementation of solutions and technological innovation, continuously iterate and optimize the performance and cost advantages of the inference system, and build the core technological barriers of the team.
7 days
- Holds a doctoral degree, with preference for candidates majoring in Computer Science, Software Engineering, or related fields.
7 days