Job description
Description
Unleash Your Potential at the Forefront of AI Innovation
At Amazon, we're on a mission to revolutionize the way the world leverages machine learning.
Amazon is seeking graduate student scientists who can turn revolutionary theory into awe-inspiring reality.
As an Applied Science Intern focused on Information and Knowledge Management in Machine Learning, you will play a critical role in developing the systems and frameworks that power Amazon's machine learning capabilities.
You'll be at the epicenter of this transformation, shaping the systems and frameworks that power our cutting-edge AI capabilities.
Imagine a role where you develop intuitive tools and workflows that empower machine learning teams to discover, reuse, and build upon existing models and datasets, accelerating innovation across the company.
You'll leverage natural language processing and information retrieval techniques to unlock insights from vast repositories of unstructured data, fueling the next generation of AI applications.
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries.
This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated.
Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward.
Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology.
Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA.
Key job responsibilities
We are particularly interested in candidates with expertise in: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages
In this role, you'll collaborate with brilliant minds to develop innovative frameworks and tools that streamline the lifecycle of machine learning assets, from data to deployed models in areas at the intersection of Knowledge Management within Machine Learning.
You will conduct groundbreaking research into emerging best practices and innovations in the field of ML operations, knowledge engineering, and information management, proposing novel approaches that could further enhance Amazon's machine learning capabilities.
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems.
A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.
A day in the life
- Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Design, development and evaluation of highly innovative ML models for solving complex business problems.
- Research and apply the latest ML techniques and best practices from both academia and industry.
- Think about customers and how to improve the customer delivery experience.
- Use and analytical techniques to create scalable solutions for business problems.
Basic Qualifications
- Are enrolled in a PhD
- Are 18 years of age or older
- Work 40 hours/week minimum and commit to 12 week internship maximum
- Can relocate to where the internship is based
- Experience programming in Java, C++, Python or related language
- Experience with one or more of the following: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages
Preferred Qualifications
- Have publications at top-tier peer-reviewed conferences or journals
- Experience building machine learning models or developing algorithms for business application
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets.
The base pay for this position ranges from $65.38/hr in our lowest geographic market up to $107.40/hr in our highest geographic market.
Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
Amazon is a total compensation company.
Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits .
This position will remain posted until filled.
Applicants should apply via our internal or external career site.
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