Amazon.com
Senior Specialist TAM – AI/ML, ES – EMEA-STAM
Job Description
At AWS Enterprise Support we are looking for a Senior Specialist Technical Account Manager (STAM) to provide unique deep-dive technical engagements for our Enterprise customers across the EMEA. You would be one of the founding members of a dynamic team bringing the latest in disruptive, cutting-edge cloud computing technologies to bear on the difficult cost and agility challenges facing many organizations.
You will provide strategic technical guidance to proactively improve performance, reliability, security and cost-effectiveness of customers’ solutions using AWS best practices. This role will focus on AI/ML AWS services such as Amazon SageMaker, Amazon Transcribe, Amazon Rekognition, and Amazon Comprehend.
This position will require the ability to travel 20% or more as needed.
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.
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.
We are open to hiring candidates to work out of one of the following locations:
Tel Aviv, ISR
Basic Qualifications
– 7+ years of design/implementation/operations/consulting with distributed applications experience
– Experience in internal enterprise or external customer-facing environment as a technical lead
– Experience with AWS services or other cloud offerings
– – Experience in the field of AI, Machine Learning, Deep Learning and related technologies.
– – Experience developing AI models in real-world environments and integrating AI/ML services into large-scale production applications
– – Experience in software development in languages like Java, Python, Scala. -Experience working with RESTful API and general service oriented architectures.
Preferred Qualifications
– Bachelor’s degree
– – Experience with operational parameters and troubleshooting for three (3) of the following: compute/storage/networking/CDN/databases/DevOps/big aata and analytics/security/applications development in a distributed systems environment
– – Internal enterprise experience working with a wide range of internal stakeholders on AIML implementations or migration with company-wide impact
– – Experience with predictive analytics, semi and unstructured data
– – Experience with AWS AIML services
– – Ability to understand complex cloud AIML environments and bridge the gap between technical and business requirements
– – Track record of implementing production AIML solutions for enterprise companies or large internet scale start-ups
– – Data science background and experience manipulating/transforming data, model selection, model training, cross-validation and deployment at scale.
– – Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and Torch.
– – Professional oral and written communication skills, presenting to an audience containing one or more decision maker(s)