Applied Scientist Ii, Aws Dynamodb

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Applied Scientist II role at Amazon AWS DynamoDB focused on developing models and algorithms for capacity utilization and data placement optimization in a large-scale NoSQL database service. The role involves identifying inefficiencies, modeling scaling bottlenecks, and creating data placement strategies to balance customer experience with resource optimization, ultimately driving production impact.

What you'd actually do

  1. Identify capacity usage optimization opportunities across the DynamoDB fleet. Quantify the customer and cost impact of each opportunity.
  2. Model the scaling bottlenecks of the service and characterize how they constrain placement and utilization.
  3. Develop data placement approaches that balance customer experience (latency, availability, throughput headroom) against optimal capacity utilization.
  4. Partner with the DynamoDB performance team to incorporate your inputs into capacity profile decisions and placement policy. Validate impact with production data.
  5. Build components that integrate directly into production systems or that directly support the large systems making placement and capacity decisions.

Skills

Required

  • building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • building models for business application experience
  • patents or publications at top-tier peer-reviewed conferences or journals
  • novel and business considerations allow

Other signals

  • models and algorithms
  • capacity utilization
  • data placement
  • fleet economics
  • customer experience