Senior Applied Scientist, Network Fabric Engineering

We are looking for an Applied Scientist to join our team and tackle some of the most challenging traffic engineering problems at planetary scale. You will develop novel optimization algorithms
and ML models that balance network utilization resilience cost efficiency and latency across traffic classes with fundamentally different characteristics. The problem then expands to network capacity planning where you will collaborate with other scientists to develop the optimal strategy to efficiently scale the network.

Key job responsibilities
- Formulate traffic engineering problems as mathematical optimization models and develop scalable solvers that operate on graphs with hundreds of nodes and O(10^4) edges
- Design ML models for traffic demand prediction anomaly detection and workload classification
- Develop capacity planning frameworks that co-optimize cost reliability and performance over multi-year horizons
- Build simulation and evaluation frameworks to validate TE algorithms against realistic failure scenarios and traffic patterns
- Publish research at top venues (SIGCOMM NSDI INFOCOM NeurIPS ICML) and contribute to the scientific community
- Collaborate with network engineers software engineers and operations teams to bring algorithms from prototype to production at global scale
- Define metrics run A/B experiments and measure the real-world impact of algorithmic changes on network performance

About the team
The Inter Data Center (InterDC) Networking team owns traffic engineering across AWSs regions the largest inter-datacenter network in the world connecting hundreds of data centers
across dozens of regions. We design and implement the algorithms optimization systems and scientific frameworks that decide how exabytes of traffic traverse this network every day. Our work
sits at the intersection of combinatorial optimization machine learning distributed systems and network engineering.

- 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 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.

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