Sr. Applied Scientist, Enterprise Engineering

Description

How often have you had an opportunity to be an early member of a team that is tasked with solving a huge customer need through disruptive, innovative technology, reinventing an industry? Are you passionate about building cutting-edge AI solutions that leverage the power of Generative AI? Do you want to be at the forefront of transforming how Amazonians work and collaborate? If so, we want to hear from you!

Our mission is to revolutionize the way Amazonians work and collaborate by transforming productivity through the power of advanced generative AI technologies. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative AI solutions, in particular those based on large language models, information retrieval, AI Agents and knowledge graphs with goals being tailored to Amazonians needs. You will handle Amazon-scale use cases with significant impact.

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 agent systems based on a rich set of structured and unstructured contextual signals

- Innovate new methods for 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

- Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in 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 about the arc of development of Agents in Amazon 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

Basic Qualifications

- 5+ years of building machine learning models for business application experience

- PhD, or Master's degree and 5+ years of applied research experience

- Experience programming in Java, C++, Python or related language

- Experience with neural deep learning methods and machine learning

Preferred Qualifications

- Experience using spark and distributed computing, for big data engineering.

- 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 and knowledge graphs

BASIC QUALIFICATIONS

- 3+ years of building machine learning models for business application experience

- PhD, or Master's degree and 6+ years of applied research experience

- Experience programming in Java, C++, Python or related language

- Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

- Experience with large scale distributed systems such as Hadoop, Spark etc.

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.

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