Description

　　Do you want to help define the future of Go to Market (GTM) at AWS using generative AI (GenAI)? 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.

　　We are open to hiring candidates to work out of one of the following locations:

　　Santa Clara, CA, USA | Seattle, WA, USA

　　Basic Qualifications

　　6+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience

　　3+ years of design, implementation, or consulting in applications and infrastructures experience

　　Bachelor’s degree in technical discipline with 5+ years of experience in software engineering, technical design, implementation, consulting experience.Experience with one or more general purpose and scripting programming languages, including but not limited to: Python, Go, C/C++, JavaScript.Experience managing ML models across training, inference, MLOPs, and/or developing AI applications.Deep hands-on understanding of deep learning and other ML algorithms and infrastructure to run them.Strong verbal and written communications skills and ability to lead effectively across organizations.Solid communication skills, business, and financial acumen.

　　Preferred Qualifications

　　5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience

　　Experience working with end user or developer communities

　　Master’s Degree or PhD in Engineering or related STEM field.5+ years of experience in technical roles in Computational Science, High Performance Computing (HPC), DevOps, performance modeling & benchmarking, Machine Learning engineering1+ years of non-internship experience training large models across compute types (e.g., GPUs, custom instances), and developing applications powered by GenAI models.2+ years of leadership experience in a technical, customer-facing role in the technology industry.Thorough understanding of the AI/ML technology stack including but not limited to: PyTorch, JAX, MegatronLM, NemoMegatron, NCCL, CUDAExperience with cloud computing, HPC technologies (Lustre, MPI, Infiniband, Slurm), containers (Kubernetes, Docker, Singularity, Enroot/Pyxis)Experience in benchmarking and performance profiling for computational applications or machine learning stacksExperience with AWS services (Amazon EC2, Amazon S3, Amazon FSx for Lustre, Amazon EFA, Amazon EBS).Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

　　Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $122,900/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.