Job Description :
Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI / ML / DL tools on Amazon Web Service (AWS)?
Come join us!
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience are driven by machine learning.
Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers.
Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning;
as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack :
1) Frameworks and Infrastructure with tools such as Apache MxNet, pyTorch, and TensorFlow,
2) Machine Learning Platforms such as Amazon SageMaker for data scientists and
3) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call.
AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping customers in Hong Kong and Taiwan design solutions that leverage our ML services.
As part of the team, you will work closely with customers to enable large-scale use cases, design ML pipelines, and drive the adoption of AWS for the ML / AI platforms.
You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage ML / AI on AWS.
Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.
The ideal candidate will be
Hands-on experiences : deep technical experiences related to artificial intelligence, machine learning and / or deep learning.
Proven abilities to build and manage modeling projects, identify data requirements, build methodology and tools that are statistically grounded.
Learn and be curious : experience with statistical analysis, data modeling, machine learning, optimizations, regression modeling and forecasting, time series analysis, data mining, and demand modeling.
Be an Architect : Ensure success in helping customers accelerate the adoption of AWS machine learning specialized services.
Guide and motivate the development of artifacts, data sheets, proof of concept best practices, and other high-value customer facing guidance and best practices.
Trusted advisor to customers : Be able to facilitate relationships with senior technical executives, as well as easily interact and give guidance to software developers, IT operations staff, and system architects.
Be able to materialize an overall recommendation (or proposal) based on customer needs and efficiently communication formal presentations, white boarding, large and small group presentations.
Vertical knowledge on industries and have related experiences (eg. manufacturing, semi-conductor, retails, over-the-top media, and telecom);
able to articulate end-to-end information flow of these focused vertical.
Have a business consultant capacity to work with customer’s line-of-business owner; explore improvement areas of customer’s business;
and priorities’ strong ROI business initiatives with customers.
Role and Responsibilities
Work with customers’ development and data science teams to deeply understand their business and technical needs and design ML solutions that make the best use of AWS SageMaker, the AWS AI Services and the AWS cloud platform.
Translate and interpret complex and interrelated datasets and correlating information into machine learning problems and meet business requirement goals.
Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions, increasing productivity, or improving sales performance.
Analyze historical data to identify trends and support decision making.
Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
Share best-practice knowledge among the solutions engineering and AWS solutions architect communities
Guide and motivate the development of artifacts, data sheets, proof of concept best practices, and other high-value customer facing guidance and best practices
Work as one-team between customers, service engineering teams, sales and support engineers
Coach and enable customers and partners to be self-sufficient
This role is a senior role in the Solutions Architecture organization at AWS. This role provides a unique opportunity to lead innovations and transformational change with large Enterprise customers in their journey to cloud.
This is HKT focused role and can be based in any of the following locations : Taipei, or Hong Kong
Job Requirements : Basic Qualifications
Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data
Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, and ability to accurately determine cause and effect relations.
3+ years of experience in design / implementation / consulting experience of Machine Learning / AI / Deep Learning solutions
3+ years of experience with one or more Deep Learning frameworks such as Apache MXNet, TensorFlow, Caffe2, Keras, Microsoft Cognitive Toolkit, Torch and Theano
3+ years vertical knowledge on industries and have related experiences
A technical degree in computer science, MIS, engineering or related discipline - or equivalent certifications / experience
5+ years of industry experience in data modeling and analysis
Experience handling terabyte size datasets and distributed training
Expert level experience with Machine Learning / AI / Deep Learning solutions for forecasting, time series analysis, data mining, and demand modeling.
Expert software architecture skills and experience building complex software systems
AWS Solutions Architecture Certification (Associate or Professional)
Demonstrated ability to think strategically about business, product, and technical challenges
Ability to gain credibility and build relationships with all levels in an organization, from technical experts to senior executives
Meets / exceeds Amazon’s functional / technical depth and complexity
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