2 days ago
Tokyo, JapanSenior
Responsibilities
- Develop and execute worldwide go-to-market strategies to accelerate adoption of AWS GenAI training and inference services.
- Work directly with customers and partners to define, implement, benchmark, and optimize scalable GenAI solutions, including proof-of-concepts and demonstrations.
- Help customers deploy and serve large language models and operate large-scale foundation-model workloads on AWS.
- Enable AWS solution architects, sales teams, and technical communities with customer-centric value propositions, technical content, and demos.
- Collaborate with engineering, product, research, sales, marketing, business development, and professional services teams to develop capabilities and influence product roadmaps.
- Communicate GenAI model capabilities, performance considerations, and implementation challenges to technical teams, stakeholders, and C-level executives.
Requirements
- At least 8 years of experience in relevant technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, or data and analytics.
- At least 3 years of experience designing, implementing, or consulting on applications and infrastructures.
- Experience developing, deploying, and managing AI products at scale.
- Experience with machine learning and large language model fundamentals, including architecture, training and inference lifecycles, and model-execution optimization, or experience with PyTorch or JAX.
- Hands-on experience benchmarking and optimizing models on GPU, TPU, or AI ASIC clusters with high-speed networking.
- Experience deploying and serving large language models for inference using container orchestration platforms such as Kubernetes.
- Hands-on understanding of deep learning, ML algorithms, and ML infrastructure, plus knowledge of MLOps tools and workflows.
- Experience working with field teams to drive adoption of ML solutions.
- Preferred qualifications include experience with end-user or developer communities, third-party AI model providers, model-hosting platforms, model APIs, and industry-specific LLM use cases.
- Preferred qualifications include a master's degree or higher in engineering or an equivalent STEM field, programming experience, strong leadership communication, cross-organizational collaboration, and the ability to influence product roadmaps.
Benefits
- AWS describes work-life flexibility and work-life harmony as part of its working culture.
- Employees have access to employee-led affinity groups, mentorship, knowledge-sharing, and career-development resources.
- Workplace accommodations and application or onboarding support are available for candidates with disabilities.
Categories
Solutions Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.