Principal AI/ML HPC TAM — Enterprise GPU & Training

Amazon Web Services (AWS); Dallas (TX); On-site; USD 183,000 - 247,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon Web Services, Inc. seeks a Principal AI/ML HPC Specialist to guide NAMER researchers and enterprise customers through complex AI HPC deployments, from distributed training on GPU clusters to production‑scale inference at scale.

You will lead deep technical engagements, architect solutions with Slurm-based scheduling, PyTorch/FSDP, SageMaker HyperPod, and NCCL optimizations, partnering with TAMs and service teams to deliver measurable business outcomes and optimized GPU utilization.

Qualifications

• 8+ years of working with Data & AI related technologies, including AI/ML, GenAI, Analytics, Database, and/or Storage experience.
• 3+ years of hands-on experience designing, implementing, or consulting on large-scale ML training or inference architectures in a customer-facing role.
• 10+ years of IT development or implementation/consulting in the software, cloud computing, or AI/ML industries.
• Demonstrated ability to serve as a trusted technical advisor to enterprise customers.

Responsibilities

• Deliver strategic technical engagements for enterprise AI/ML workloads, including distributed training architectures.
• Architect and validate production‑grade AI/ML training/inference solutions using Slurm, PyTorch, DeepSpeed, and SageMaker HyperPod.
• Enable customer success with MLOps pipelines, distributed data processing, and cluster observability.
• Drive business outcomes with capacity planning, NCCL optimization, and proactive monitoring.

Skills

AI/ML architectures

Technical advisory

Distributed training

Cloud computing

Tools

PyTorch

TensorFlow

MXNet

Job description

Amazon Web Services, Inc. seeks a Principal AI/ML HPC Specialist to guide NAMER researchers and enterprise customers through complex AI HPC deployments, from distributed training on GPU clusters to production‑scale inference at scale.

You will lead deep technical engagements, architect solutions with Slurm-based scheduling, PyTorch/FSDP, SageMaker HyperPod, and NCCL optimizations, partnering with TAMs and service teams to deliver measurable business outcomes and optimized GPU utilization.