Job description
Description
Shape the Future of Human-Machine Interaction
Are you a master of natural language processing, eager to push the boundaries of conversational AI?
Amazon is seeking exceptional graduate students to join our cutting-edge research team, where they will have the opportunity to explore and push the boundaries of natural language processing (NLP), natural language understanding (NLU), and speech recognition technologies.
Imagine waking up each morning, fueled by the excitement of tackling complex research problems that have the potential to reshape the world.
You'll dive into production-scale data, exploring innovative approaches to natural language understanding, large language models, reinforcement learning with human feedback, conversational AI, and multimodal learning.
Your days will be filled with brainstorming sessions, coding sprints, and lively discussions with brilliant minds from diverse backgrounds.
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 Natural Language Processing & Speech Applied Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA.
Key job responsibilities
We are particularly interested in candidates with expertise in: NLP/NLU, LLMs, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning.
In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Natural Language Processing and Speech Technologies.
You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on natural language processing, speech recognition, text-to-speech (TTS), text recognition, question answering, NLP models (e.g., LSTM, transformer-based models), signal processing, information extraction, conversational modeling, audio processing, speaker detection, large language models, multilingual modeling, and more.
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 novel, scalable algorithms and modeling techniques that advance the state-of-the-art in natural language processing, speech recognition, text-to-speech, question answering, and conversational modeling.
- Tackle groundbreaking research problems on production-scale data, leveraging techniques such as LSTM, transformer-based models, signal processing, information extraction, audio processing, speaker detection, large language models, and multilingual modeling.
- Collaborate with cross-functional teams to solve complex business problems, leveraging your expertise in NLP/NLU, LLMs, reinforcement learning, human feedback/HITL, deep learning, speech recognition, conversational AI, natural language modeling, and multimodal learning.
- Thrive in a fast-paced, ever-changing environment, embracing ambiguity and demonstrating strong attention to detail.
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: Natural Language Processing/Understanding, Large Language Models, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning
Preferred Qualifications
- Have publications at top-tier peer-reviewed conferences or journals
- Experience in designing experiments and statistical analysis of results
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
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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