Amazon Development Center U.S., Inc.
Technology
SeniorAppliedScientist,AgenticWorkSpaces
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Applied Scientist, Agentic WorkSpaces at Amazon Development Center U.S., Inc.. Skills: Machine learning, Capacity management, Demand forecasting, Resource optimization. Architect ML foundations. Implement ML foundations”
What You'll Achieve.
ML systems enable profitability; Reduce capacity waste; Improve cost efficiency; Eliminate customer-impacting events; Unlock significant cost savings; Maintain safety margins; Enable autonomous decision-making
Industry & Context.
Ambiguous problems; Complex business requirements; Capacity risks; Demand volatility
What They're Looking For.
Must Have
3+ years building ML models, PhD or Master's degree, 6+ years applied research experience, Programming in Java, C++, Python, Experience with neural deep learning, Experience with machine learning
Nice to Have
Experience with R, Experience with scikit-learn, Experience with Spark MLLib, Experience with MxNet, Experience with Tensorflow, Experience with numpy, Experience with scipy
What You'll Do.
Architect ML foundations
Implement ML foundations
Build forecasting systems
Build anomaly detection systems
Design optimization algorithms
Partner with product teams
Translate product vision
Work on capacity forecasting problems
Identify research challenges
Deliver with limited guidance
Drive alignment on ML approaches
Drive alignment on capacity strategies
Develop end-to-end solutions
Deliver end-to-end solutions
Make technical trade-offs
Lead on business problems
Shape ML research direction
Propose new approaches
Set example with solutions
Set example with code
Set example with designs
Set example with artifacts
How You'll Work.
Team & Collaboration
Product and engineering teams; Product managers; Business stakeholders; Engineering teams; Operations teams
Full Job Description
About the Organization AWS is on a mission to transform how businesses operate by delivering intelligent, cloud-powered applications. Our Applied AI Solutions organization accelerates customer success through intuitive, differentiated technology that solves enduring business challenges — blending vision with real-world expertise to build turnkey solutions that are easy to adopt and built to scale. Within this organization, we are building the next generation of secure, intelligent workspaces — environments purpose-built for human-AI collaboration at enterprise scale. The Role We are looking for a Senior Applied Scientist to build the predictive intelligence powering capacity management for our workspace platform — developing machine learning systems that forecast demand, optimize resource allocation, and enable cost-efficient scaling at massive scale. This role requires someone who can translate complex business requirements into production ML systems, designing algorithms that balance customer experience with operational efficiency across a large and diverse fleet of capacity pools. What You'll Do • Architect and implement ML foundations for capacity management, building models that continuously learn and optimize across multiple dimensions including geography, platform, and instance type. • Develop demand forecasting systems that anticipate usage patterns hours to weeks in advance, enabling proactive capacity decisions at scale. • Build anomaly detection systems that identify capacity risks before they impact customers, improving service reliability and resilience. • Design optimization algorithms that make high-frequency, automated decisions balancing two critical forces: ensuring a flawless customer experience where every operation succeeds, while maximizing cost efficiency through intelligent resource utilization and placement strategies. • Apply advanced ML techniques including time-series forecasting, reinforcement learning, and causal inference to measure th
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