Alibaba Cloud-System Engineer, Machine Learning-Sunnyvale

Required: . BS, MS, or Ph.D. in Computer Science, Computer Engineering, or related field; . At least 3-5 years industry experience or relevant experience; . Experience with ML Architectures and hardware accelerators, e.g. Nvidia GPU; . Experience in machine learning frameworks and deep learning toolsets; . Ability to work independently, good communication and strong interpersonal skills; . Reliability and self-motivation in a dynamic product-oriented team; Desirable: . Knowledge of CPU/GPU architecture; . Experience in large scale machine learning distributed training process; . Knowledge of deep learning model algorithm and architecture; The pay range for this position at commencement of employment is expected to be between $156,000 and $256,800/year.

However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Sinian team focuses on heterogeneous compute and software-hardware cooperative technologies. We have worked on a unified heterogeneity-aware lowering and optimization platform, accelerating applications on various heterogeneous hardware.

Our goal is to unleash the hardware computing power and deploy deep learning applications for improving portability, performance, and utilization. Your responsibilities include, but are not limited to: . Installation, configuration and bring-up of vendor machine learning hardware . Providing operational support for prototype hardware and software system including validation and troubleshooting . Troubleshoot and resolve any system-related issues arising during model training and deployment . Performance analysis, profiling and benchmarking of machine learning workloads running on system . Collaborate with production team to distill the requirements . Independently solving complex technical and logistical problems in a fast-paced environment