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AWS Cloud Support Engineer (SageMaker, Vision and Other), Support Engineering, Dublin
Client:
Amazon Web Services EMEA SARL (Irish Branch) - G50
Location:
Dublin, Ireland
Job Category:
Other
EU work permit required:
Yes
Job Reference:
20372bcc25c8
Job Views:
5
Posted:
19.04.2025
Expiry Date:
03.06.2025
Job Description:
As a Cloud Support Engineer you will learn at an accelerated pace how to use and leverage many different cloud technologies to help our customers succeed. You will act as the Cloud Ambassador across AWS products, providing our customers with required tools and tactics to scale their impact in world-wide markets.
The Big Data (SageMaker, Vision and Other) role supports our services that leverage data and develop AI/ML applications, which include training, finetuning and deploying machine learning and deep learning models on cloud using our AI/ML services like SageMaker, Bedrock, Textract, Rekognition, etc. In this role, engineers interact with customers that reach out to AWS via email, chat or phone. Helping our customers use and integrate Big Data services in what is arguably our industry’s most exciting space. Engineers also focus on hiring and developing Subject Matter Expertise in one or more services. Engineers collaborate with internal teams to provide the required support services to AWS customers. In addition, engineers work on team functions and automation/optimization projects and continually work on improving operational efficiency.
AWS Sales, Marketing, and Global Services (SMGS) 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. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Key job responsibilities:
* You will be primarily responsible for solving customer’s cases through a variety of contact channels (telephone, email, and web/live chat), applying advanced troubleshooting techniques to provide tailored solutions and working with them to dive deep into the root cause of an issue.
* You will drive initiatives that improve support-related processes and our customers’ experience. These can include tutorials, how-to videos, technical articles, trainings, among others.
* You will leverage your customer support experience to provide feedback to internal AWS teams on how to improve our services, and work on critical, highly complex customer problems that may span multiple AWS services.
* You will be continuously learning new and innovative technologies, and developing new technical skills and other professional competencies.
* You will act as interviewer in hiring processes, and coach/mentor new team members.
PLEASE NOTE: This role requires the flexibility to work 5 days a week (occasionally on weekends) on a rotational basis. Schedules may align to Sunday - Thursday, Tuesday – Saturday or Monday - Friday.
About the team
AWS Support Engineering is a customer-facing global organization that provides technical support to our customers as well as our internal teams. As a member of our team, you will be at the forefront of this transformational technology, operating on a follow-the-sun model. You will be 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.
About AWS
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
* 1+ years of software development, or 1+ years of technical support experience
* Experience troubleshooting and debugging technical systems
* Knowledge or experience in Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI) and GenAI. Experience with Networking and troubleshooting (TCP/IP, DNS, OSI model, routing, switching, firewalls, LAN/WAN, traceroute, iperf, dig, cURL or related). Good understanding of OS concepts (memory, storage, and CPU usage)
PREFERRED QUALIFICATIONS
* Knowledge or experience in data science or similar role involving data extraction, analysis, statistical modeling, communication experience and troubleshooting.
* Experience using notebook solutions such as Jupyter to conduct reproducible data analysis and modeling projects.
* Knowledge or experience using scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) and hands-on experience building models with deep learning/machine learning frameworks like TensorFlow, Keras, PyTorch, MXNet.
* Analysis and troubleshooting skills and experience.
* Understanding of cloud computing concepts and/or experience with any cloud platforms (AWS, Azure, Google Cloud).
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