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Applied Scientist, Generative AI Innovation Center
1 mese fa
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
The primary responsibilities of this role are to:
• Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries
• Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them
• Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution
About the team
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and fine-tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
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 flexible work hours and arrangements are part of our 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:
Rome, RM, ITA
BASIC QUALIFICATIONS
Several years of building models for business application experiencePhD, or Master's degree and several years of CS, CE, ML or related field experience
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
Experience in professional software developmentPhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field
Practical experience in solving complex problems in an applied environment
Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, or PyTorch
Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
Comfortable working in a fast paced, highly collaborative, dynamic work environment
Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
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