Job Information
Amazon Principal Data Scientist, Model Evaluation, GenAI, AWS in Singapore, Singapore
Description
Are you passionate about Generative AI (GenAI)? In this role, you will help our customers build and deploy GenAI enabled applications using Amazon Bedrock and SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.
The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which 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. We work backwards from our customer’s most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you'll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam
The Generative AI and Machine Learning (GenAI/ML) team guides AWS customers on building enterprise-grade GenAI systems. This role will support development of an architectural blueprint that our customers can use to build their own enterprise-wide Generative AI platforms, which will help them balance democratization of access to GenAI and speed of innovation with following best practices around trustworthy AI, cost efficiency, security, etc. This role specifically will be responsible for development of implementation best practices and architectural guidance for performing model evaluation, benchmarking and regression testing using existing and novel metrics. The role will partner with others on the team to develop comprehensive and authoritative portfolio-wide guidance for AWS GenAI customers. The role will also collaborate with model evaluation framework providers in OSS and academia. The deliverables include: contributions to the joint architectural blueprint / whitepaper, completion of sample model benchmarks, thought leadership in the form of public writing and speaking, as well as internal enablement. The role has a global remit.
Key job responsibilities
Customer Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers and with the academic community.
Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements.
Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures.
#GenAI
Basic Qualifications
7+ years design/implementation/consulting experience of distributed applications
5+ years management of technical, customer facing resources
5+ years of hands-on experience with AI/ML or related technology domain
5+ years of hands-on experience with AI/ML model evaluation and evolution or similar
Preferred Qualifications
History of successful technical consulting and/or architecture engagements with large-scale customers or enterprises
Experience migrating or transforming legacy customer solutions to the cloud
Track record of thought leadership and innovation around Model Evaluation.
Presentation skills with a high degree of comfort speaking with executives, IT Management, and developers.
Computer Science /relevant degree and/or experience highly desired