Senior Applied Scientist, Leo Security

Amazon Leo is a constellation of Low Earth Orbit satellites that will provide low-latency high-speed broadband network connectivity to unserved and underserved communities around the world.

We are looking for an Applied Scientist to be a founding scientist on the Engineering and R&D team within Leo Infrastructure and IP Security. The team defends the manufacturing lines launch sites and global ground infrastructure behind the constellation from the most sophisticated threat actors on the planet. These requirements create open scientific problems at the intersection of agentic AI real-time stream processing graph-based reasoning and behavioral analytics. You will build the science behind a neurosymbolic reasoning platform and the models that detect the behavior of sophisticated threat actors. This is an R&D role with a production mandate where you define the problem rather than solve a pre-scoped one and every model detection and agent workflow you build becomes the system Leos security teams use to protect the constellation.

#### Export Control Requirement

Due to applicable export control laws and regulations candidates must be a U.S. citizen or national U.S. permanent resident (i.e. current Green Card holder) or lawfully admitted into the U.S. as a refugee or granted asylum.


Key job responsibilities
- Design and implement scalable production-grade neurosymbolic systems that integrate symbolic reasoning over graph-based knowledge representations with LLM agents to deliver reliable verifiable security outcomes.
- Design and run reinforcement learning and fine-tuning pipelines (GRPO PPO DPO) to optimize language models for security reasoning triage and detection-authoring tasks.
- Build behavioral and statistical models that detect threat actor behavior and design the evaluation frameworks that measure model performance against that behavior before trusting a model in production.
- Design and build multi-agent systems that autonomously triage enrich and contain security events including the constrained reasoning safety guardrails and validation mechanisms that make automated decisions trustworthy at scale.
- Own the end-to-end science lifecycle from research and experimentation through production deployment defining the metrics that measure system performance and real-world security impact.
- Advance the state of the art through publications at top-tier venues patents or open-source contributions and shape the scientific agenda and research culture from day one.


A day in the life
You will move between research and production in the same week: framing an ambiguous security problem as a scientific question prototyping an approach and partnering with software engineers to ship it as a capability the platform runs continuously. Security engineers on your team translate threat intelligence into the adversary behaviors that matter; you build the models that detect those behaviors and evaluate model performance against them. You will obsess over the two latencies that define the platforms the time from event to detection and the time from detection to containment action and design agents and detections that drive both down. You will backtest candidate detections against retained telemetry review evaluation results before a model or agent capability graduates to automated execution and deliver scientific artifacts that ship.


About the team
Leo Infrastructure and IP Security protects the people facilities hardware and supply chain behind a global satellite constellation. The Engineering and R&D team within this organization builds the platforms and tooling the security pillar teams operate on moving security operations from manual triage to correlation-based detection automated response and agentic AI. The team is composed of applied scientists software engineers and security engineers working across physical and digital security domains.

#### Inclusive Team Culture

In Amazon Security its in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas perspectives and voices.

#### Training & Career Growth

Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing training and other career-advancing resources here to help you develop into a better-rounded professional.

#### Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home theres nothing we cant achieve.


- 3 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 graph algorithms knowledge graphs unsupervised learning (clustering dimensionality reduction anomaly detection) NLP and embedding-based retrieval
- - Experience designing evaluation frameworks for AI systems where ground truth requires human judgment including staged rollouts A/B testing and expert feedback loops

- Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
- Experience in building quantitative solutions as a scientist or science manager
- Experience in one or more of the following domains: access- control system and methodology network security application- and system-development security security architecture and models cryptography and operations security
- - Experience with terabyte-scale stream processing and real-time correlation of heterogeneous event sources
- - Experience with cost and latency optimization for LLM-based systems (token reduction schema optimization deterministic offloading)
- - Publications in applied ML graph analytics agentic AI or security analytics

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 167100.00 - 226100.00 USD annually