Data Scientist, GenAI Innovation Center
3 weeks ago
As a data scientist, you have deep and broad experience as an ML practitioner. You interface directly with customers to understand and identify their challenges that can be addressed by Generative AI. You build secure solutions that can scale to the size of the problem at hand and guide customers through your rigorous evaluation process. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You're part of both a small team dedicated to public sector customers and a global organization enabling customers to accelerate their progress on GenAI.
This position requires that the candidate selected be a US Citizen.
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.
A day in the life
1. Team with a GenAI strategist to understand a customer problem and provide guidance on how and whether GenAI can help address the issue.
2. Share your latest experiment results or challenges with other scientists on the team.
3. Collaborate on a blog post to share the results and methods used in your most recent customer success.
4. Attend or a deliver a tech talk to highlight a project you or a team mate just completed.
5. Provide feedback to your team during a code review.
6. Meet with customer stakeholders to demonstrate the latest progress on their problem.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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 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.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Denver, CO, USA
BASIC QUALIFICATIONS
- 3+ years of experience building models for business applications- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning
- Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet
- Bachelor's degree and 5 years of experience or Master's degree and 2 years of experience
PREFERRED QUALIFICATIONS
- PhD or Masters 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 with deep learning (e.g., CNN, RNN, LSTM, Transformer)
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