Overview As an Applied Scientist on AWS's Traffic and Network Modeling team, you translate complex infrastructure problems into scalable ML-driven solutions that guide capacity planning and topology decisions. You will collaborate with network engineers and software teams to deliver low-latency forecasts and production-ready models. This role combines rigorous research with practical engineering to impact a world-leading cloud network. You'll work in an inclusive, knowledge-sharing culture that values bold ideas and ownership.
Compensation / Benefits- health insurance
- 401(k) matching
- paid time off
- parental leave
- RSUs
- sign-on payments
Responsibilities- Drive hypothesis-driven research to inform roadmap decisions for network traffic modeling
- Build and deploy production-grade ML models and forecasting systems for network demand and capacity planning
- Own problems end-to-end from understanding networking needs to delivering scalable solutions
- Raise the bar through scientific rigor, code reviews, and knowledge sharing
- Tackle ambiguous, high-impact challenges and drive them to a conclusion
- Collaborate across network engineers, software engineers, and other scientists to design customer-focused solutions
- Work backwards from customer problems to fast, scalable designs
Key requirements- 3+ years building models for business applications
- PhD, or Master's +4 years in CS/CE/ML or related field
- Experience with patents or publications at top-tier venues
- Programming proficiency in Java, C++, Python or related languages
- Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel & distributed computing, high-performance computing
- Cross-functional collaboration
- Strong scientific rigor and continuous learning
- Mentorship and knowledge sharing
- ML modeling for forecasting and optimization
- Production systems development for low-latency predictions
- Numerical optimization and data mining
