Sr. Applied Scientist AWS Catalog, AWS Catalog

This is a chance to work at the front of data security and governance with Amazon scale impact on customers. As a Sr. Applied Scientist III you bring your education experience and expertise in formal methods programming languages and automated reasoning to the permissions model behind AWSs data catalog so that customers can state precisely who may see which data and trust that the answer holds wherever that data is read. Experience with LLMs multi-agent workflows and structured guardrails that raise determinism in LLM output is a this role you join a strong group of applied scientists in a highly supportive environment with real cognitive safety and room to grow.

Key job responsibilities
You combine deep expertise in programming languages and automated reasoning to design the language and the formal semantics customers use to express permissions over catalog resources down to the level of individual columns and rows. The model has to stay correct compact expressive enough for real customer intent explainable when it denies a request and exhaustively testable. Much of the difficulty is navigating ambiguity to balance those properties against each other. You write clear narratives and documentation that enumerate the design choices and build consensus quickly.

You lead design and delivery of scientifically complex components that are rarely revisited once shipped and that deliver measurable customer benefit. The problems are concrete: proving that a change to a policy cannot expand access beyond what the author intended deciding whether two policies written in different models grant the same thing showing that a fast evaluation path on the request hot path agrees with the reference semantics and keeping permissions faithful to intent as schemas and data evolve underneath them. You maintain detailed knowledge of your teams systems and proactively drive improvements in efficiency and consistency across team boundaries.

You influence your teams science and business strategy collaborating with Applied Scientists Engineers and Product Managers across identity storage analytics and machine learning teams and contributing to roadmaps goals and priorities. You harmonize discordant views and build consensus through thoughtful feedback. Beyond your team you apply advanced techniques to bottleneck problems and are regarded as a reliable creative problem solver. You further AWSs academic influence through publications talks and advancing the state of the art in data security governance programming languages and automated reasoning.

About the team
The team owns the permissions layer of AWSs data catalog. That covers 1/ the model and formal semantics customers use to author permissions across catalogs databases tables columns and rows 2/ the evaluation path that turns those permissions into an authorization decision on every request under latency budgets that leave no room for a slow answer 3/ the detection and resolution of divergence between what a customer intended and what is actually enforced as resources change over time and 4/ converging existing permission models onto one including the reasoning needed to show that a migration preserves a customers access boundaries. The team works closely with identity storage and analytics teams across AWS.

- 6 years of building machine learning models for business application experience
- PhD or Masters 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

- 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 an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

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The base salary range for this position is listed below. As a total compensation company Amazons package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon offers comprehensive benefits including health insurance (medical dental vision prescription basic life & AD&D insurance) Registered Retirement Savings Plan (RRSP) Deferred Profit Sharing Plan (DPSP) paid time off and other resources to improve health and well-being. We thank all applicants for their interest however only those interviewed will be advised as to hiring status.

CAN BC Vancouver - 195900.00 - 327200.00 CAD annually