Job Information
Amazon Sr. AI/ML Specialist Solutions Architect in Bangkok, Thailand
Description
Are you passionate about Machine Learning (ML), Deep Learning and Artificial Intelligence (AI)? Are you excited by the challenge of driving production usage of ML and AI? Come join us!
ML and AI, especially Generative AI are rapidly growing in importance. We’re seeing more and more amazing AI work being done from home automation and mobile apps to financial trading and shipping logistics. Given the scale required for developing AI models, the cloud is an ideal place to deploy AI models, and Amazon Web Services (AWS) is the leader in the deployment of AI. We’re looking for someone passionate and deeply excited about this space. Someone who is devoted to helping customers understand how AI can make a big difference to their businesses.
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.
Candidates must have great communication skills and be very technical, with the ability to impress AWS customers at any level, from executives to developers. Previous experience with AWS is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior engineers at customers, partners and AWS service teams, influencing their roadmaps and driving innovation.
If you are someone who enjoys innovating, likes solving hard problems and working on the cutting edge of technology, we would love to have you on the team.
Sales, Marketing and Global Services (SMGS)
AWS Sales, Marketing, and Global Services (SMGS) 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. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
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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.
Architect solutions leveraging AWS machine learning, AI and Generative AI specific services, working closely with customers to deeply understand their business needs and design technical solutions that optimize the use of the AWS Cloud platform and AI/ML Services.
Serve as a thought leader by crafting and developing compelling, audience-specific messages and assets (e.g., product videos, customer success stories, demos, presentations, how-to guides) to showcase AWS services and technologies through forums such as AWS Blogs, Workshops, Reference Architectures, and public-speaking events like AWS Summits and User-Group events. Capture and share best practices and insights internally, as well as with partners and customers.
Develop and support an internal AWS community of AI/ML Subject Matter Experts, fostering knowledge-sharing and collaboration.
Collaborate with AWS business development, professional services, training, and support teams to help partners and customers effectively learn and use AWS services.
Serve as a key member of the business development and account management team, ensuring customer success on the AWS platform. Act as a technical liaison between customers, service engineering teams, and support, providing updates on customer progress and ensuring plan execution by partners.
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
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. 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.
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.
Basic Qualifications
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.
Preferred Qualifications
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.