As a Senior Principal Scientist in AGI, you will have deep subject matter expertise in the area of large language models and generative AI across various modalities. You will work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables. More specifically, you will provide thought leadership on and lead strategic efforts in Responsible AI efforts for AGI, covering themes including but not limited to AI Safety, Privacy, and Bias/Fairness, and work with Product, Science, and Engineering teams to deliver short- and long-term RAI solutions in production for a broad class of large-scale models. You will liaise with internal partners (e.g. AWS, Amazon Security, various Amazon businesses leveraging AGI capabilities), as represent Amazon/AGI in external engagements with regulatory bodies and government agencies (e.g. NIST AI Safety Institute) on the topic of Responsible AI. Finally, you will work with academic partners to support our in-house talent with direct access to cutting edge research and mentoring.

BASIC QUALIFICATIONS

Graduate degree in Computer science/Math or related field.
Experience in building complex, real-time systems involving AI, ML, and NLP with successful delivery to customers.
Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements. Ability to take a project from requirements gathering and design to actual product launch
Computer Science fundamentals in data structures, algorithm design and complexity analysis.
Ability to develop machine learning platform strategy in the subdomain of recommender systems for streaming services.
Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead science efforts to meet aggressive timelines with optimal solutions.
Demonstrated track record of peer-reviewed scientific publications that advance state-of-the art for applied science.

PREFERRED QUALIFICATIONS

15+ years of relevant, broad research experience after PhD degree or equivalent.
Deep expertise in Machine Learning as applied to large-scale generative models, with focus on RAI technologies
Proficiency in programming for algorithm and code reviews.
Strong core competency in mathematics and statistics.
Track record of successful projects in algorithm design and product development.
Publications at top-tier peer-reviewed conferences or journals.
Strong prior experience with mentorship and/or management of senior scientists and engineers.
Thinks strategically, but stays on top of tactical execution.
Exhibits excellent business judgment; balances business, product, and technology very well.
Effective verbal and written communication skills with non-technical and technical audiences.
Experience working with real-world data sets and building scalable models from big data.


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 $240,100/year in our lowest geographic market up to $350,000/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.