Sr. Applied Science, Agentic WorkSpaces (AAWS)

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box making complex things easy and hard things possible with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction and we are looking for builders who share that mindset.


Within AAIS Amazon WorkSpaces is our cloud based virtual desktop service that delivers secure managed computing to over one million daily users across the globe enabling organizations to provision manage and scale desktops with the reliability and performance their workforce depends on.


We are looking for a Senior Applied Scientist to own and advance the science behind capacity modelling for Amazon WorkSpaces. You will design build and continuously improve the forecasting and optimization models that ensure the right compute storage and networking resources are available at the right time in the right regions at the lowest possible cost without ever compromising the end user experience.


This is a high impact individual contributor role for someone who thrives at the intersection of applied research and production systems. You will define the scientific roadmap for capacity intelligence turning reactive provisioning into a predictive self optimizing engine that anticipates demand before customers feel any constraint.

Key job responsibilities
Define and drive the scientific strategy for capacity modelling establishing the research agenda that transforms how WorkSpaces forecasts demand plans supply and allocates resources across a globally distributed infrastructure.
Build advanced demand forecasting models that predict workspace usage across multiple time horizons from intraday spikes to long range growth trajectories incorporating signals such as customer onboarding patterns seasonal trends regional expansion and macroeconomic indicators.
Design supply optimization frameworks that determine optimal resource placement instance mix and pre warming strategies balancing availability performance and cost by reasoning over hardware constraints pricing dynamics and service level objectives.
Develop causal and probabilistic models that move beyond trend extrapolation to true understanding of demand drivers enabling the organization to distinguish organic growth from one time events anticipate shifts in usage patterns and quantify uncertainty in planning decisions.
Architect simulation and scenario planning systems that allow business and engineering leaders to run what if analyses stress test capacity plans against disruption scenarios and evaluate trade offs between investment timing risk tolerance and customer experience.
Pioneer the integration of machine learning with operations research combining deep learning based forecasting with mathematical optimization to jointly solve the demand prediction and resource allocation problem in a way that neither discipline can achieve alone.
Establish evaluation frameworks and monitoring systems that measure forecast accuracy capacity utilization and cost efficiency in production creating tight feedback loops that drive continuous model improvement and build organizational trust in science driven planning.
Influence the broader organizations capacity strategy by translating model outputs into actionable recommendations for leadership identifying opportunities to extend capacity intelligence patterns to adjacent services and mentoring scientists and engineers across the team.

About the team
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.


Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.


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 in the cloud.


Here at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity and AmazeCon conferences inspire us to never stop embracing our uniqueness.


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

- 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

Required Experience:

Senior IC

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