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About the Role
Join the Amazon Web Services (AWS) Support team as a strategic partner in delivering Amazon AI/ML solutions to empower Frontier AI customers to innovate, optimize, and achieve operational excellence. You will be at the forefront of solving complex AI/ML model training and inference implementation challenges, guiding customers through their machine learning transformation journeys.
Responsibilities
- Deliver Strategic Technical Engagements — Lead comprehensive technical deep-dives and performance optimization for enterprise AI/ML workloads.
- Architect and Validate Innovative Solutions — Support customers in designing and implementing production-grade AI/ML training and inference solutions.
- Enable Customer Success — Support customers in implementing business-critical HPC capabilities.
- Enable Business Critical Outcomes — Partner with service teams to enhance model training throughput, optimize NCCL collective communications, and improve GPU/Trainium utilization.
- Serve as Trusted Advisor and Advocate — Develop and nurture technical partnerships with enterprise stakeholders, serving as the trusted advisor for AI/ML infrastructure decisions.
Requirements
- 5+ years of design/implementation/operations/consulting with distributed applications experience
- 5+ years of technical engineering experience
- Bachelor's degree in computer science, engineering, mathematics or equivalent, or 4+ years of technical work experience
- 7+ years of technical engineering experience
- Experience in a 24x7 operational services or support environment
- Experience in internal enterprise or external customer-facing environment as a technical lead
- 5+ years of experience in AI/ML, distributed computing, or GPU-accelerated infrastructure (e.g., model training, inference systems, HPC for ML)
- Familiarity with SageMaker HyperPod for managed distributed training clusters including automated health checks, node replacement, and checkpoint-based recovery
- Experience with HPC job schedulers (Slurm, PBS, LSF) for orchestrating multi-node ML training workloads
- Experience with high-performance parallel file systems (Amazon FSx for Lustre, GPFS/Spectrum Scale) for ML data pipelines
- Familiarity with AWS Parallel Computing Service (PCS), AWS ParallelCluster, AWS Batch, or equivalent managed HPC/ML cluster services
- Professional oral and written communication skills, presenting to an audience containing one or more executive team member(s)
Skills
- AI/ML
- HPC
- Distributed applications
- GPU-accelerated infrastructure
- Model training
- Inference systems
- SageMaker HyperPod
- HPC job schedulers (Slurm, PBS, LSF)
- High-performance parallel file systems (Amazon FSx for Lustre, GPFS/Spectrum Scale)
- AWS Parallel Computing Service (PCS)
- AWS ParallelCluster
- AWS Batch
- NCCL
- EFA
- SRD
- PyTorch FSDP
- DDP
- DeepSpeed
- Megatron-LM
- SageMaker HyperPod
- Amazon FSx for Lustre
- Deep Learning AMIs (DLAMIs)
- P6e UltraServers
- AWS Neuron SDK
- Large language model (LLM)
- Physics-informed neural networks (PINNs)
- MLOps pipelines
- AWS Step Functions
- AWS Batch
- EC2
- S3
- DDB
- RDS
Location
- USA, CA, San Francisco
Work Type
- Onsite
Experience Level
- Sr. TAM
- 5+ years of design/implementation/operations/consulting with distributed applications experience
- 5+ years of technical engineering experience
- 7+ years of technical engineering experience
- 5+ years of experience in AI/ML, distributed computing, or GPU-accelerated infrastructure
Education Level
- Bachelor's degree in computer science, engineering, mathematics or equivalent
Salary/Compensations
- 176,600.00 - 239,000.00 USD annually
Benefits
- Sign-on payments
- Restricted stock units (RSUs)
- Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- Paid time off
- Parental leave
About the Company
- Amazon Web Services (AWS) is seeking an experienced Sr. TAM with expertise in AI/ML, HPC, and/or other technologies to join our Frontier AI Technical Account Management (TAM) team.
- The Frontier AI Enterprise Support team supports our complex Startup customers who are building large AI training, inference models, and requires high GPU demand. We help these Frontier research labs scale fast.
- We are a collaborative group of technical innovators dedicated to pushing the boundaries of cloud computing and artificial intelligence.
- Our team thrives on solving complex challenges — from optimizing NCCL all-reduce operations across hundreds of GPUs to architecting elastic training clusters that scale with customer demand.
- We believe in continuous learning, mutual support, and driving technological advancement.
- Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- Our inclusive culture empowers Amazonians to deliver the best results for our customers.
Equal Opportunity
- Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
- San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
- If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.