Sr. Specialist, GenAI, Model Training & Inference - Amazon

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, developing GTM plans, external/internal evangelism, and developing demos and proof-of-concepts. Key job responsibilities In this role, you will work closely with customers to understand the ML infrastructure requirements, complexities involved in scaling GenAI model training across modalities and use-cases like natural language processing (NLP) and computer vision that take advantage of the power of AWS' storage, compute, networking, and ML technologies. You will have the opportunity to define GTM strategies and lead cross-functional initiatives to expand existing markets, develop scalable programs to drive adoption, and identify new opportunities. This involves activities include market sizing, building an opportunity pipeline, working with customers to understand technical requirements for proof-of-concepts, creating content to train the field teams, driving industry thought-leadership, working with product teams to define new features, and identifying partners and potential acquisitions. As the ideal candidate, you possess a business and technology background that enables you to lead and drive engagements with startups and large enterprises. You have domain expertise in key ML use cases, understand the challenges involved in training and deploying GenAI models, orchestrating workloads using containers/HPC services, and are able to work backwards from customer requirements to suggest scalable solutions and architectures. You have the technical depth to articulate the benefits of ML Frameworks and AWS services to data scientists, data engineers, and C-Level executives. In addition, you have a good understanding of the GenAI market trends, ecosystem, opportunities, and are passionate about market development. You will need to be adept at interacting, communicating, and partnering with teams within AWS (product, solutions architecture, sales, marketing, and professional services) and externally with customers, partners, and importantly, the developer community of ML Frameworks and key open-source offerings. You will be responsible for creating compelling content, and building scalable programs and mechanisms to increase awareness and adoption of ML Frameworks and AWS solutions. 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: Austin, TX, USA | New York, NY, USA | Santa Clara, CA, USA | Seattle, WA, USA Basic Qualifications - 5+ years of developing, negotiating and executing business agreements experience - Experience developing strategies that influence leadership decisions at the organizational level - Experience managing programs across cross functional teams, building processes and coordinating release schedules - Bachelor's degree in technical discipline with 7+ years of technical design / implementation / consulting experience. - 5+ years of business development, product management, management consulting, and strategic partnership experience. - Experience developing and executing on GTM strategies that are large in scope. - Working knowledge of one or more ML Frameworks (e.g., PyTorch, JAX) and ML methods including GenAI foundation models, computer vision models, and other ML models. Preferred Qualifications - Experience interpreting data and making business recommendations - Experience identifying, negotiating, and executing complex legal agreements - MBA/MS or equivalent relevant business experience. - Experience working with GenAI Foundation models, part of startups working on GenAI foundation models across modalities. - Hands-on working knowledge of deep learning and other ML algorithms and infrastructure. - 7+ years of pre-sales engineering, technical business development, strategic partnerships, or program/product management experience - Experience with cloud computing and or related fields. - Demonstrated ability to work effectively across internal and external organizations is key in a matrix environment. - Strong verbal and written communications skills and ability to lead effectively across organizations. - Experience speaking at technology conferences, as well as communicating across the organization from technical staff to VP/CxOs. 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 $118,400/year in our lowest geographic market up to $220,200/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.