Principal Scientist for Generative AI Innovations
2 weeks ago
Join Our Team as a Senior Applied Scientist in Generative AI
Are you ready to shape the future of Generative AI (GenAI) on AWS by utilizing your extensive expertise in applied sciences? As a key member of our global Generative AI models team, you will integrate your scientific knowledge with customer interactions to deliver tailored GenAI solutions on AWS.
About the Worldwide Specialist Organization (WWSO)
The WWSO is an integral part of AWS Sales, Marketing, and Global Services (SMGS), dedicated to driving revenue and growth across a diverse range of customers, from small and mid-market accounts to large enterprises, including public sector entities. Our approach focuses on understanding and addressing our customers' most complex challenges, enabling us to develop and execute effective go-to-market strategies that transform AWS concepts into substantial business opportunities.
Your Role and Responsibilities
As a Senior Applied Scientist specializing in GenAI, you will be instrumental in enhancing our portfolio of third-party models on AWS. Your responsibilities will include:
- Facilitating the integration and benchmarking of new third-party models.
- Engaging with customers and model providers at a high technical level to deliver insights and solutions that meet their GenAI needs.
- Advocating for and implementing robust system designs for GenAI applications, ensuring they are scalable, reliable, and high-performing.
You will stay updated on the latest developments in the GenAI ecosystem, AWS services, and industry best practices through continuous research and solution development, maintaining a competitive edge in your field.
Qualifications
To be successful in this role, you should possess:
- A PhD or Master's degree with at least 6 years of applied research experience.
- A minimum of 3 years of experience in building machine learning models for business applications.
- Proficiency in programming languages such as Java, C++, or Python.
- Experience with neural deep learning methods and machine learning frameworks.
Preferred Qualifications
Additional qualifications that would be advantageous include:
- Familiarity with modeling tools like R, scikit-learn, Spark MLLib, MxNet, TensorFlow, numpy, and scipy.
- Experience with large-scale distributed systems such as Hadoop and Spark.
Commitment to Diversity
Amazon is dedicated to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other legally protected status.
Compensation
Our compensation structure reflects the labor market across various US geographic regions. The base salary for this position ranges from $150,400 to $260,000, depending on market location and individual qualifications. In addition to base pay, we offer a comprehensive compensation package that may include equity, sign-on bonuses, and a full range of medical and financial benefits.
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