דרושים Data Center Technical Support Technician ב-אמזון ב-China, Beijing

Key job responsibilities
- Act as a thought leader sharing best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re: Invent, etc.We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

- 5+ years design and implementation experience with NoSQL technologies and Key-value stores such as ElastiCache, Aerospike, Redis, Memcached, including NoSQL data modeling.
- 3+ years software architecture and development experience using languages such as Java, Python, Go, and Node.js
- - A degree in computer science, software engineering, or mathematics or 10 years equivalent work experience.
- - Knowledge of the underlying infrastructure requirements such as Networking, Storage, and Hardware Optimization.
- - Demonstrated effectiveness working across multiple business units to achieve results.
- - An understanding of computing deployment models as they relate to databases and analytics.
- - Working knowledge of modern software development practices such as agile methodologies and DevOps.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

*Hiring location: Beijing, Shanghai, Guangzhou, Shenzhen, Hong Kong(visa sponsorship provided)As a Senior Technical Account Manager (Sr. TAM) specializing in GPU Optimization in AWS Enterprise Support, you will play a crucial role in two key missions: guiding customers' GPU acceleration initiatives across AWS's comprehensive compute portfolio, and spearheading the development of optimization strategies that revolutionize customer workload performance.Key Job Responsibilities
- Design and optimize GPU resource usage on EC2/EKS/SageMaker or equivalent cloud compute, container, and ML services; implement node pool tiering, Karpenter/Cluster Autoscaler tuning, auto scaling, and cost governance (Savings Plans/RI/Spot/ODCR or equivalent).
- Drive GPU partitioning and multi-tenant resource sharing strategies to reduce idle resources and increase overall cluster utilization.- Build GPU observability and monitoring systems (nvidia-smi, CloudWatch or equivalent monitoring tools, profilers, distributed communication metrics) to align capacity planning with SLOs.
- Ensure compatibility across GPU drivers, CUDA, container runtimes, and frameworks; standardize change management and rollback processes.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- 5+ years in cloud technical support, solutions architecture, or customer success management, with at least 3 years of hands-on experience in GPU/accelerated computing platforms.
- In-depth understanding of GPU instance families (e.g., AWS G/P/H series) or similar offerings from other cloud providers, AMI/driver/CUDA/container compatibility management, and cloud storage/network performance tuning (e.g., S3 I/O, EBS/Instance Store equivalents, preprocessing pipelines). Proficient in scheduling GPU workloads with EKS or equivalent Kubernetes-based orchestration services, including node pool tiering, resource quotas, elastic scaling, and auto-recovery strategies. Experienced in multi-GPU/multi-node distributed computing (NCCL, topology awareness, tensor parallelism, pipeline parallelism) with expertise in communication optimization for large-scale AI training and inference.
- Skilled in PyTorch/TensorFlow performance analysis and optimization, including DataLoader tuning, mixed precision, operator fusion, and inference acceleration toolchains (ONNX, TensorRT, CUDA Graphs).
- Experienced in cost and capacity governance, familiar with Savings Plans, RI, ODCR, Spot, Capacity Blocks, and right-sizing strategies or their equivalents in other cloud platforms.
- Demonstrated cross-functional communication and influence skills, capable of driving technical solutions with data and business objectives.

- AWS Solutions Architect Professional, Machine Learning Specialty, or DevOps Professional certification or equivalent credentials from other cloud providers.
- Hands-on experience with NVIDIA ecosystem software and toolchains (CUDA/cuDNN/NCCL, TensorRT, CUDA Graphs) and proven ability to maintain performance consistency across versions and platforms.
- Delivered quantifiable performance improvements (GPU throughput, latency reduction, cost savings) with demonstrated benchmarking and regression testing methodology.
- Proven repeatable optimization results in LLM inference, batch AI training, real-time video processing, or high-performance computing (HPC).
- Contributions to open source projects (Run:ai, Ray, vLLM, DeepSpeed, Kubeflow, etc.) or published technical articles, whitepapers, or performance benchmarking.
- Experience with Infrastructure as Code (Terraform, AWS CDK **or equivalent cloud development frameworks**), Helm Charts, baseline container image management, and DevOps automation.
- Able to present performance-business tradeoffs and results to senior stakeholders using PR/FAQ documents, architecture diagrams, and capacity/cost reports.

Key job responsibilities
1. Generative AI Model Development:
-Design and develop generative AI models, including language models, image generation models, and multimodal models.
-Explore and implement advanced techniques in areas such as transformer architectures, attention mechanisms, and self-supervised learning.
-Conduct research and stay up-to-date with the latest advancements in the field of generative AI.2. Data Acquisition and Preprocessing:
-Identify and acquire relevant data sources for training generative AI models.
-Develop robust data preprocessing pipelines, ensuring data quality, cleanliness, and compliance with ethical and regulatory standards.
-Implement techniques for data augmentation, denoising, and domain adaptation to enhance model performance.3. Model Training and Optimization:
-Design and implement efficient training pipelines for large-scale generative AI models.
-Leverage distributed computing resources, such as GPUs and cloud platforms, for efficient model training.
-Optimize model architectures, hyperparameters, and training strategies to achieve superior performance and generalization.4. Model Evaluation and Deployment:
-Develop comprehensive evaluation metrics and frameworks to assess the performance, safety, and bias of generative AI models.
5. Collaboration and Knowledge Sharing:-Contribute to the firm's thought leadership by presenting at conferences, and participating in industry events.About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
- 4+ years of experience in developing and deploying machine learning models, with a strong focus on generative AI techniques.
- Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks.
- Strong background in natural language processing, computer vision, or multimodal learning.
- Ability to communicate technical concepts to both technical and non-technical audiences.

- Experience with large language models, such as Claude, GPT, BERT, or T5.
- Familiarity with reinforcement learning techniques and their applications in generative AI.
- Understanding of ethical AI principles, bias mitigation techniques, and responsible AI practices.
- Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Apache Spark, Dask).
- Strong problem-solving, analytical, and critical thinking skills.
- Strong communication, collaboration, and leadership skills.

Every day will bring new and exciting challenges on the job while you:- Make recommendations on AI architecture, security, cost optimization, and operational excellence- Complete analysis and present periodic reviews of AI workload performance- Foster an ecosystem where AI and humans progress together through knowledge sharingDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- Master's degree in Computer Science, Artificial Intelligence, Machine Learning or related technical field
- Deep understanding of Generative AI fundamentals, Large Language Models, and core AI/ML concepts
- Excellent theoretical foundation in AI technologies and their underlying principles
- Excellent empirical reasoning skills with ability to formulate theories, make predictions, validate and refine solutions

- PhD in Computer Science, Artificial Intelligence, Machine Learning or related field
- Demonstrated ability to build systematic knowledge frameworks across technology stacks
- Experience with implementing enterprise-scale AI/ML solutions
- Experience with AWS core services across Compute, Storage, Database, and Networking
- Knowledge of cloud architecture patterns and distributed systems, cloud security principles and compliance frameworks
- Experience with container technologies and serverless architectures, modern software development practices and DevOps
- Excellence in stakeholder management and technical communication

Key job responsibilities
What you will do:* You set technical priorities to align with your organization’s business strategy.
* You are a technical leader. You set the standards for other support engineers.
* You know how to break down problems into sub problems that can be worked in parallel by other Support Engineers.
* You partner with HW/SW Engineering and Quality Assurance teams to drive projects to completion.
* You lead retrospectives of error, drive improvements, ensure long term resolution.
* You look for patterns, build repeatable solutions, identify opportunities to improve Operation Excellence of the labs.

Basic Qualifications* You use Linux commands and ADB commands as fluently as typing your own name and address.
* You are hands-on in using and troubleshooting host software (Ubuntu OS), usual ports and protocols on smart devices (USB, HDMI, Switch, Router, AP, PDU, KVM, Dongle, Wireless protocols, networking, firewalls, securities, etc.)
* You not only can root an Android device, but also understand how it works.
* You can write efficient scripts in a language like Python/C/C++.
* You read software logs and identify problems even if the logs were not authored by you.
* Bachelor’s degree; 8+ years working in a similar, hands-on role.

Preferred Qualifications* Experience as an IT/Network support engineer
* Can build a web application or tool with consideration of its supportability, scalability, and performance.
* Knowledge in software architecture, networking performance and security.
* Hands-on experience in software testing.
* Experience in using the AWS Cloud (IAM, VPC, EC2, RDS, System Manager, SES, etc.)

Key job responsibilities
What you will do:* You set technical priorities to align with your organization’s business strategy.
* You are a technical leader. You set the standards for other support engineers.
* You know how to break down problems into sub problems that can be worked in parallel by other Support Engineers.
* You partner with HW/SW Engineering and Quality Assurance teams to drive projects to completion.
* You lead retrospectives of error, drive improvements, ensure long term resolution.
* You look for patterns, build repeatable solutions, identify opportunities to improve Operation Excellence of the labs.

Basic Qualifications* You use Linux commands and ADB commands as fluently as typing your own name and address.
* You are hands-on in using and troubleshooting host software (Ubuntu OS), usual ports and protocols on smart devices (USB, HDMI, Switch, Router, AP, PDU, KVM, Dongle, Wireless protocols, networking, firewalls, securities, etc.)
* You not only can root an Android device, but also understand how it works.
* You can write efficient scripts in a language like Python/C/C++.
* You read software logs and identify problems even if the logs were not authored by you.
* Bachelor’s degree; 8+ years working in a similar, hands-on role.

Preferred Qualifications* Experience as an IT/Network support engineer
* Can build a web application or tool with consideration of its supportability, scalability, and performance.
* Knowledge in software architecture, networking performance and security.
* Hands-on experience in software testing.
* Experience in using the AWS Cloud (IAM, VPC, EC2, RDS, System Manager, SES, etc.)

Key job responsibilities
What you will do:* You set technical priorities to align with your organization’s business strategy.
* You are a technical leader. You set the standards for other support engineers.
* You know how to break down problems into sub problems that can be worked in parallel by other Support Engineers.
* You partner with HW/SW Engineering and Quality Assurance teams to drive projects to completion.
* You lead retrospectives of error, drive improvements, ensure long term resolution.
* You look for patterns, build repeatable solutions, identify opportunities to improve Operation Excellence of the labs.

- 4+ years of software development, or 4+ years of technical support experience
- Experience scripting in modern program languages
- Experience troubleshooting and debugging technical systems
- Experience in agile/scrum or related collaborative workflow
- Experience troubleshooting and documenting findings

- Knowledge of distributed applications/enterprise applications
- Knowledge of UNIX/Linux operating system
- Experience analyzing and troubleshooting RESTful web API calls