Senior AI Model Customization & Optimization Lead

Amazon Web Services (AWS); East Palo Alto (CA); Presencial; USD 193.000 - 262.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

401(k) matching

Paid time off

Parental leave

Descripción de la vacante

Amazon Web Services (AWS) seeks a Senior Forward Deployed Engineer for the Custom Models & Optimization team. You will be the technical lead embedded inside strategic customers, shaping model customization, optimization, and production deployment to achieve measurable business outcomes in quality, latency, and cost.

You will design distributed training and RL post-training systems, migrate workloads to AWS Trainium, and drive architectural decisions while mentoring a team of engineers and

Formación

• 5+ years of professional software development experience
• Experience training, fine-tuning, or optimizing deep learning models

Responsabilidades

• Lead the technical engagement embedded with the customer across multiple workstreams
• Define customization strategy to meet quality, latency, and cost targets
• Architect training and inference systems at scale for large models
• Lead migrations to AWS Trainium and optimize performance and成本
• Mentor FDEs and scientists, participate in hiring and design reviews
• Identify reusable patterns and influence AWS service roadmaps
• Own delivery plan, milestones, and risk management

Conocimientos

Technical leadership

Mentorship

Model optimization

Communication to executives

Distributed training

Educación

Bachelor's degree in computer science or equivalent

Herramientas

PyTorch FSDP2

Megatron-LM

Miles

verl

NeMo-RL

OpenRLHF

SkyRL

TRL

SGLang

vLLM

TensorRT-LLM

CUDA

Triton

NKI

Descripción del empleo

Amazon Web Services (AWS) seeks a Senior Forward Deployed Engineer for the Custom Models & Optimization team. You will be the technical lead embedded inside strategic customers, shaping model customization, optimization, and production deployment to achieve measurable business outcomes in quality, latency, and cost.

You will design distributed training and RL post-training systems, migrate workloads to AWS Trainium, and drive architectural decisions while mentoring a team of engineers and