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Amazon
Austin, TX; Seattle, WA; Santa Clara, CA; New York, NY
Source: Amazon careers · View original posting
From Amazon's posting. “We” and “our” refer to the employer.
Do you want to help define the future of Go to Market (GTM) at AWS using generative AI (GenAI)?
AWS Worldwide Specialists Org (WWSO) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
You will be part of the core worldwide GenAI Training and Inference team, responsible for defining, building, and deploying targeted strategies to accelerate customer adoption of our services and solutions across industry verticals.
You will be working directly with the most important customers (across segments) in the GenAI model training and inference space helping them adopt and scale large-scale workloads (e.g., foundation models) on AWS, model performance evaluations, develop demos and proof-of-concepts, developing GTM plans, external/internal evangelism, and developing demos and proof-of-concepts.
Key job responsibilities
You will help develop the industry’s best cloud-based solutions to grow the GenAI business. Working closely with our engineering teams, you will help enable new capabilities for our customers to develop and deploy GenAI workloads on AWS. You will facilitate the enablement of AWS technical community, solution architects and, sales with specific customer centric value proposition and demos about end-to-end GenAI on AWS cloud.
You will possess a technical and business background that enables you to drive an engagement and interact at the highest levels with startups, Enterprises, and AWS partners. You will have the technical depth and business experience to easily articulate the potential and challenges of GenAI models and applications to engineering teams and C-Level executives.
This requires deep familiarity across the stack – compute infrastructure (Amazon EC2, Lustre), ML frameworks PyTorch, JAX, orchestration layers Kubernetes and Slurm, parallel computing (NCCL, MPI), MLOPs, as well as target use cases in the cloud.
You will drive the development of the GTM plan for building and scaling GenAI on AWS, interact with customers directly to understand their business problems, and help them with defining and implementing scalable GenAI solutions to solve them (often via proof-of-concepts). You will also work closely with account teams, research scientists, and product teams to drive model implementations and new solutions.
You should be passionate about helping companies/partners understand best practices for operating on AWS. An ideal candidate will be adept at interacting, communicating and partnering with other teams within AWS such as product teams, solutions architecture, sales, marketing, business development, and professional services, as well as representing your team to executive management. You will have a natural appetite to learn, optimize and build new technologies and techniques.
You will also look for patterns and trends that can be broadly applied across an industry segment or a set of customers that can help accelerate innovation.
This is an opportunity to be at the forefront of technological transformations, as a key technical leader. Additionally, you will work with the AWS ML and EC2 product teams to shape product vision and prioritize features for AI/ML Frameworks and applications. A keen sense of ownership, drive, and being scrappy is a must.
The Frameworks team specializes in computational workloads, performance evaluation, and optimization. We partner with foundation model builders, large-scale training customers, and physical AI innovators to solve complex challenges across the full ML stack. Our expertise spans hardware (GPUs, Custom Silicon), operating systems, communication libraries (NCCL, MPI), frameworks (PyTorch, NeMo, JAX), and models (Llama, Nemotron).
We also support physical AI workloads involving real-time inference, robotics simulation, and sensor data pipelines. Additionally, we work with containers (Docker, Enroot), orchestrators (EKS), and schedulers (Slurm) to deliver scalable, high-performance solutions for the most demanding AI applications.
Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience working with PyTorch or JAX software
10+ years of technical specialist, design and architecture experience, or degree in advanced technology
Experience in computer architecture, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
Experience deploying and serving large language models for inference using container orchestration platforms like Kubernetes.
Hands-on understanding of deep learning and other ML algorithms and infrastructure.
Knowledge of MLOps tools and workflows for model development, validation, and deployment.
Experience working with field teams to drive adoption of ML solutions.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.
Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
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