Applied Scientist

Sunnyvale, California, USA

Applications have closed

Amazon.com

Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...

View all jobs at Amazon.com

The Amazon Artificial General Intelligence (AGI) Personalization team is looking for a passionate, highly skilled and inventive Applied Scientist with strong machine learning background to build state-of-the-art ML systems for personalizing large-scale, high-quality conversational assistant systems. As a Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graph, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences.

Key job responsibilities
- Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals
- Innovate new methods for contextual knowledge extraction and information retrieval, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, compute, latency and quality
- Research in advanced customer understanding and behavior modeling techniques
- Collaborate with cross-functional teams of scientists, engineers, and product managers to identify and solve complex problems in personal knowledge aggregation, processing, modeling, and verification
- Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results
- Think Big on conversational assistant system personalization 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

About the team
The AGI Personalization org uses various contextual signals to personalize Large Language Model output for our customers while maintaining privacy and security of customer data. We work across multiple Amazon products, including Alexa, to enhance the user experience by bringing more personal context and relevance to customer interactions.

Basic Qualifications


- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 2+ years of building models for business application experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

- Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Proficient in 2 of these areas: large language models, information retrieval, recommender systems, knowledge graph, and graph neural networks.

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/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.

Job stats:  2  0  0
Category: Data Science Jobs

Tags: AGI Data Mining Deep Learning Java LLMs Machine Learning MXNet NLP PhD Privacy Python Recommender systems Research Security TensorFlow

Perks/benefits: Career development Conferences Equity / stock options

Region: North America
Country: United States

More jobs like this