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 optimise robotic picking routes in our fulfilment centres.
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 like Apache MxNet 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 New Zealand 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.
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 machine learning 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.
Your roles and responsibilities will include :
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.
Thought Leadership Evangelise AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Singapore Summit, AWS re : Invent, etc.
Partner with SAs, Sales, Business Development and the AI / ML Service teams to accelerate customer adoption and revenue attainment in New Zealand of Amazon SageMaker.
Act as a technical liaison between customers and the AWS SageMaker services teams to provide customer driven product improvement feedback.
Contribute to the development and support of an AWS internal community of ML related subject matter experts.
Job Requirements : Basic Qualifications
3+ years of experience in design / implementation / consulting for 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
5+ years professional experience in software development in languages related to ML like Python or R. Experience working with RESTful API and general service-oriented architectures
3+ years of experience in technical architecture, design, deployment and operations for AI platforms, standards, protocols and devices
Graduate degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.)
5+ years of industry experience in predictive modeling and analysis · Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relationships
Consulting experience and track record of helping customers with their AI needs
Publications or presentation in recognised Machine Learning, Deep Learning and Data Mining journals / conferences
Experience with AWS technologies like Sagemaker, Redshift, S3, EC2, Data Pipeline, Kinesis & EMR
Knowledge of SparkML
Able to write production level code, which is well-written and explainable
Experience using ML libraries, such as scikit-learn, caret, mlr, mllib
Experience working with GPUs to develop models
Experience handling terabyte size datasets
Track record of diving into data to discover hidden patterns
Familiarity with using data visualisation tools
Knowledge and experience of writing and tuning SQL
Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
Experience giving data presentations
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