The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (Gen. AI) technologies that can handle Amazon-scale use ca... more details
DESCRIPTION
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities.
As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences.
Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA | Cambridge, MA, USA | New York, NY, USA | Sunnyvale, CA, USA
BASIC QUALIFICATIONS
- PhD, or Master's degree and 5+ years of applied research experience - 5+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
PREFERRED QUALIFICATIONS
- PhD in Computer Science, Machine Learning, or a related field, with a focus on Gen AI and reinforcement learning - Demonstrated experience in developing and implementing algorithms and models for supervised fine-tuning and reinforcement learning through human feedback - Strong programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch - Excellent problem-solving skills, with the ability to think creatively and critically about complex problems - Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams - Experience with patents or publications at top-tier peer-reviewed conferences or journals
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year 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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