Amazon Sr AI/ML Specialist Solutions Architect 

Thailand, Bangkok, Bangkok 

350959840

As an AI/ML Specialist Solutions Architect (SA), you will be the Subject Matter Expert (SME) for designing machine learning solutions that leverage AWS services to automate solutions and drive down costs for customers. Part of the Data and AI Specialist Solutions Architecture team, you will work closely with the other Specialist SAs on Big Data, Databases and Analytics, as well as the Business Development teams, to enable large-scale customer use cases and drive the adoption of AWS for AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop technical content, reference implementations, and presentations to enable customers, partners and ISVs to fully leverage AI/ML and Generative AI on AWS. You will also create field enablement materials for the broader SA population, to help them understand how to integrate AWS AI/ML and Generative AI solutions into customer architectures.You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred, in addition to experience building complex classification models. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help AWS customers in their selection process.Sales, Marketing and Global Services (SMGS)
Key job responsibilities
- Build and maintain technical trusted advisor relationships with influential technical decision-makers to drive the successful adoption and deployment of AWS services and technologies.
About the team
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
Work/Life BalanceMentorship 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.

- Deep experience in the design, implementation, and delivery of Machine Learning, AI, Deep Learning, and Generative AI solutions, with a strong understanding of AI-related technologies and the ability to develop effective AI models in real-world environments.
- Significant expertise in creating, testing, and deploying ML models, as well as developing AI solutions, with a passion for hands-on coding using DL platforms/tools like MXNet, Caffe, Caffe2, Theano, and TensorFlow.
- Solid grounding in statistics, probability theory, data modelling, machine learning algorithms, and software development techniques and languages used to implement analytics solutions, with 5+ years of professional experience in software development in languages like Python or R.
- Extensive experience with data modelling and analytics solution stacks, as well as a deep understanding of AI platforms, standards, protocols, and devices, with strong technical architecture, design, deployment, and operational-level knowledge.
- Excellent verbal and written communication skills, the ability to work effectively across internal and external organizations and distributed teams, and the talent to influence and build mindshare convincingly with any audience, including the ability to create compelling demonstrations of AI solutions and experience in public speaking to large audiences.

- 5+ years of consultative technical pre-sales or professional services experience with a proven track record of success.
- Ability to build credible relationships and communicate effectively with all levels of an organization, from technical experts to senior executives.
- 3+ years of hands-on experience working with cloud platforms like AWS or other virtualization technologies.
- 3+ years of experience working directly with enterprise customers.
- Expertise in predictive analytics, semi-structured and unstructured data, and deployment of production-grade machine learning solutions on public cloud platforms.
- Advanced degree in computer science, engineering, or mathematics, with a strong background in data science, machine learning, and neural networks. Hands-on experience with relevant tools and a continuous interest in academic developments in this space is highly desirable.