Are you passionate about Artificial Intelligence, Machine Learning, Deep Learning and Generative AI? Do you want to build state of the art solutions using AWS AIML services for some of AWS biggest customers? Would you like a career that gives you opportunities to help customers and partners that use cloud computing services to run their AIML solutions reliably, securely, efficiently and at lower cost?
Key job responsibilities
AWS Enterprise Support is looking for a Senior AIML Specialist Technical Account Manager (STAM) to provide unique deep-dive AIML technical engagements for Enterprise customers across ASEAN. You will be a member of a dynamic team bringing the latest in disruptive, cutting-edge AIML technologies, focused on enabling organisations to adopt AWS AIML services to drive their businesses
A day in the life
In this deeply technical and consultative role, you will provide strategic people, process and technology guidance to ensure enterprise support customers realise the benefits of AIML and Generative AI, whilst embedding operational excellence from day 1. You will partner with TAMs, SAs and service teams to provide customers with AWS AIML best practice guidance, diving deep into AIML services, promoting customers AIML workloads to production, developing regional AIML strategies, and training field teams on the use cases and benefits of generative AI.
About the team
Diverse Experiences
AWS 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.
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 & 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.
Basic qualifications
- Experience in internal enterprise or external customer-facing environment as a technical lead
- Experience with AWS services or other cloud offerings
- Extensive experience in the field of AI, Machine Learning, Deep Learning and related technologies.
- Extensive experience developing AI models in real-world environments and integrating AI/ML services into large-scale production applications
- Professional experience in software development in languages like Java, Python, Scala. Experience working with RESTful API and general service oriented architectures.
- Professional oral and written communication skills, presenting to an audience containing one or more decision maker(s)
Preferred qualifications
- Internal enterprise experience working with a wide range of internal stakeholders on AIML implementations or migration with company-wide impact
- Experience with predictive analytics, semi and unstructured data
- Experience with AWS AIML services
- Ability to understand complex cloud AIML environments and bridge the gap between technical and business requirements
- Track record of implementing production AIML solutions for enterprise companies or large internet scale start-ups
- Data science background and experience manipulating/transforming data, model selection, model training, cross-validation and deployment at scale.
- Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and Torch.
