Principal Research Scientist

2 weeks ago

Santa Clara, California, United States Amazon Full time

Join Our Innovative Team

Become a part of the AWS AI science team, where we are dedicated to developing cutting-edge models for intelligent automation.

About AWS Utility Computing

AWS Utility Computing (UC) is at the forefront of product innovation, offering foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2). Our commitment to consistently delivering new product innovations sets AWS apart in the cloud services industry.

Your Role

As a member of the UC organization, you will play a vital role in the development and management of services across Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Applications within AWS. You will also support customers requiring specialized security solutions for their cloud services.

Impactful Research Opportunities

At AWS, we are a leading provider of cloud services, enabling the creation and growth of numerous businesses. You will have the chance to tackle real-world challenges, leveraging vast data and computational resources while collaborating with world-class engineers and developers to bring your innovative ideas to fruition. We expect you to devise groundbreaking solutions to complex problems and share your research at peer-reviewed conferences and workshops.

Qualifications We Seek

We are in search of exceptional researchers with expertise in one or more of the following domains: autonomous agents, large multimodal models (particularly vision-language models), reinforcement learning (RL), and sequential decision-making.

Team Environment

AWS values diverse experiences. We encourage candidates from various backgrounds to apply, regardless of whether they meet all qualifications listed. If your career path is non-traditional or includes alternative experiences, we welcome your application.

Why Choose AWS?

Amazon Web Services (AWS) is the most comprehensive and widely adopted cloud platform globally. We pioneered cloud computing and continue to innovate, earning the trust of customers ranging from successful startups to Global 500 companies.

Inclusive Culture

At AWS, we embrace a culture of learning and curiosity. Our employee-led affinity groups promote inclusion and celebrate our differences. We host ongoing events and learning experiences, such as Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, to inspire us to appreciate our uniqueness.

Mentorship and Growth

We are committed to raising our performance standards as we strive to become Earth’s Best Employer. You will find ample opportunities for knowledge-sharing, mentorship, and career advancement resources to help you grow as a well-rounded professional.

Work-Life Harmony

We prioritize work-life balance. Achieving success at work should not come at the expense of personal life, which is why we promote flexibility in our work culture. When we feel supported both at work and home, we can achieve remarkable results in the cloud.

Flexible Work Options

We value innovation and recognize that it often requires uninterrupted focus. We also appreciate in-person collaboration. Our team offers options for employees to work in the office daily or adopt a flexible, hybrid work model.

Basic Qualifications

  • PhD or Master's degree with 6+ years of applied research experience
  • 3+ years of experience in building machine learning models for business applications
  • Proficiency in programming languages such as Java, C++, Python, or related languages
  • Experience with neural deep learning methods and machine learning

Preferred Qualifications

  • Familiarity with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, numpy, scipy, etc.
  • Experience with large-scale distributed systems like Hadoop, Spark, etc.

Amazon is committed 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 other legally protected status.

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