Amazon
Applied Scientist II, Artificial General Intelligence
Amazon, Boston, Massachusetts, us, 02298
DESCRIPTION
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in deep learning, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems.
Key job responsibilities
As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. Your work will directly impact our customers in the form of products and services that make use of AI technology. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in order to provide the best-possible experience for our customers.
BASIC QUALIFICATIONS
PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience1+ years of building models for business application experienceExperience programming in Java, C++, Python or related languageExperience with deep learning techniquesExperience with LLM model training and fine-tuning
PREFERRED QUALIFICATIONS
Experience with popular deep learning modeling tools and workflows such as MxNet, TensorFlow, R, scikit-learn, Spark MLLib, numpy, and scipy.Experience with deep learning modeling techniques including CNNs, RNNs, GANs, VAEs, and Transformers.Experience with conducting research in a corporate settingExperience in scientific publications at top-tier peer-reviewed conferences or journals.Highly effective verbal and written communication skills with both non-technical and technical audiences.Experience with conducting applied research in a corporate setting.Experience in building deep learning models for business application.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
#J-18808-Ljbffr
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in deep learning, to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems.
Key job responsibilities
As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. Your work will directly impact our customers in the form of products and services that make use of AI technology. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in order to provide the best-possible experience for our customers.
BASIC QUALIFICATIONS
PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience1+ years of building models for business application experienceExperience programming in Java, C++, Python or related languageExperience with deep learning techniquesExperience with LLM model training and fine-tuning
PREFERRED QUALIFICATIONS
Experience with popular deep learning modeling tools and workflows such as MxNet, TensorFlow, R, scikit-learn, Spark MLLib, numpy, and scipy.Experience with deep learning modeling techniques including CNNs, RNNs, GANs, VAEs, and Transformers.Experience with conducting research in a corporate settingExperience in scientific publications at top-tier peer-reviewed conferences or journals.Highly effective verbal and written communication skills with both non-technical and technical audiences.Experience with conducting applied research in a corporate setting.Experience in building deep learning models for business application.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
#J-18808-Ljbffr