Job description

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. About the team The Frameworks team is highly specialized on computational workloads, performance evaluations and optimization. We work with Foundation model builders and large scale training customers, dive deep into the ML stack including the hardware (GPUs, Custom Silicon), operating system (kernel, communication libraries (NCCL, MPI), Frameworks (PyTorch, NeMO, Jax) and models (Llama, Nemotron...). We also work with containers (Docker, Enroot), orchestrators (EKS) and schedulers (Slurm). Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 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. 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. Mentorship and 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. - 7+ 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 - Experience developing, deploying and managing AI products at scale - 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 - Bachelor’s degree in technical discipline with 10+ years of technical design / implementation / consulting experience. - Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking. - 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. - Master's degree or above in engineering or equivalent STEM (Science, Technology, Engineering and Mathematics) field - Experience with at least one general-purpose programming language such as Java, Python, C++, C#, Go, Rust, or TypeScript - Experience communicating clearly and concisely with leadership, stakeholders, and cross-functional teams - Experience working with end user or developer communities - Experience working with 3rd party AI model providers to evaluate model quality/performance. - Experience deploying models on model hosting platforms and/or working with early adopters of model APIs. - Knowledge of vertical use cases for large language models in industries like finance, healthcare, retail etc. - Demonstrated ability to work effectively across internal and external organizations. - Ability to influence product roadmaps based on customer needs and market traction. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit amazon.jobs for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. 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 amazon.jobs . USA, CA, Mountain View - 176,600.00 - 239,000.00 USD annually USA, NY, New York - 169,000.00 - 228,600.00 USD annually USA, TX, Austin - 153,600.00 - 207,800.00 USD annually USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually

Requirements

Must-haves

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.
Key job responsibilities
About the team
Diverse Experiences
Work/Life Balance
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.
Mentorship and Career Growth
7+ 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
Experience developing, deploying and managing AI products at scale
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
Bachelor’s degree in technical discipline with 10+ years of technical design / implementation / consulting experience.
Hands-on experience benchmarking and optimizing performance of models on accelerated computing (GPU, TPU, AI ASICs) clusters with high-speed networking.
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.
Master's degree or above in engineering or equivalent STEM (Science, Technology, Engineering and Mathematics) field
Experience with at least one general-purpose programming language such as Java, Python, C++, C#, Go, Rust, or TypeScript
Experience communicating clearly and concisely with leadership, stakeholders, and cross-functional teams
Experience working with end user or developer communities
Experience working with 3rd party AI model providers to evaluate model quality/performance.

Nice-to-haves

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Keywords to mirror

goawsaimlkubernetesdockermachine learningjavapythonrusttypescript

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave