Description

Are you a customer-obsessed builder with a passion for helping customers achieve their full potential? Do you have the business savvy, GenAI Training and Inference background, and sales skills necessary to help position AWS as the cloud provider of choice for customers? Do you love building new strategic and data-driven businesses? Join the Worldwide Specialist Organization (WWSO) Frameworks ML team as a Business Development Specialist!

The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which 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. We work backwards from our customer’s most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you'll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam.

Key job responsibilities

The worldwide GenAI Training and Inference team is 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.

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.

About the team

• Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

• Mentorship & Career Growth: We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

• Work/Life Balance: We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

• Inclusive Team Culture: Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

• Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Basic Qualifications

• 7+ years of relevant GTM, Sales, or Consulting experience.

• 5+ years’ experience in distributed, multi-node, multi-GPU model training.

• 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.

• BA/BS degree required.

Preferred Qualifications

• Exceptional interpersonal and communication (both written and verbal) skills.

• Experience communicating with both technical and non-technical stakeholders across multiple teams, as well as internal and external executive stakeholders.

• Established track record of credibility as a technology advisor with customer executives (e.g. CEO, COO, CIO, CTO, CMO) and Line of Business Leaders.

• Experience and success in negotiating complex deals with customers and partners.

• Experience in a heavily matrixed sales environment, including developing, implementing, managing, and executing go-to-market growth initiatives and sales motions.

• Deep understanding of cloud technologies, including public and hybrid cloud platforms.

• Technical background in engineering, computer science, or MIS a plus.

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 $133,200/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.