Amazon | Cloud Support Engineer

Vor 6 Tagen

Sydney, Österreich Tideri Jobbörse Vollzeit

Cloud Support Engineer - Sagemaker, Vision & other, Support Engineering ABOUT US
Amazon Web Services is the market leader and technology forerunner in the Cloud business.
As a member of the AWS Support team, you will be at the forefront of this transformational technology, assisting a global list of companies and developers that are taking advantage of a growing set of services and features to run their mission-critical applications.
As a Cloud Support Engineer, you will act as the 'Cloud Ambassador' across all the cloud products, arming our customers with required tools & tactics to get the most out of their Product and Support investment.
Would you like to use the latest cloud computing technologies?
Do you have an interest in helping customers understand application architectures and integration approaches?
Are you familiar with best practices for applications, servers, and networks?
Do you want to be part of a customer-facing technology team helping to ensure the success of Amazon Web Services (AWS) as a leading technology organization?

WHAT CAN YOU EXPECT FROM A LIFE AT AWS?
Every day will bring new and exciting challenges on the job while you:

Learn and use groundbreaking technologies.
Apply advanced troubleshooting techniques to provide unique solutions to our customers' individual needs.
Interact with leading engineers around the world.
Partner with Amazon Web Services teams to help reproduce and resolve customer issues.
Leverage your extensive customer support experience to provide feedback to internal AWS teams on how to improve our services.
Drive customer communication during critical events.
Drive projects that improve support-related processes and our customers' technical support experience.
Write tutorials, how-to videos, and other technical articles for the developer community.
Work on critical, highly complex customer problems that may span multiple AWS services.
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.

Minimum Requirements

Good depth of understanding in Machine Learning concepts, such as common ML algorithms and their uses and data preparation techniques.
Good depth of understanding in Hadoop Administration, support, and troubleshooting (Any two applications: Apache Spark, Apache Hive, Presto, Map-Reduce, Zookeeper, HBASE, HDFS, and Pig.)
Good understanding of Linux and Networking concepts and Intermediate programming/scripting skills.
Ideally in Java or Python, but will consider experience in other Object Oriented and Functional languages.
Intermediate to advanced expertise in Machine Learning experience: supervised learning (regression), supervised learning (classification).
Experience with data preparation techniques for training.
Experience with training models, hyperparameter tuning, hosting, and deployment of models.
Good Understanding of common ML algorithms such as Linear Learner, Decision Trees, Kmeans, etc.
Experience with one or more ML Frameworks such as Tensorflow, Pytorch, etc.
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