Amazon.com Inc logo

Applied Scientist II - AMZ9971140

Amazon.com Inc

  • Seattle, WA
  • 19 days ago
  • $153,456–$193,200 Per Year
Want to know if you’re a fit?
Upload your resume and let our AI show you.

Skills

  • Access Controlunmatched
  • Algorithmsunmatched
  • Amazon Web Services (AWS)unmatched
  • Analysis Skillsunmatched
  • Artificial Intelligence (AI)unmatched
  • Bayesian Networksunmatched
  • Best Practicesunmatched
  • C++ Programming Languageunmatched
  • Cloud Computingunmatched
  • Computer Scienceunmatched
  • Computer Systemsunmatched
  • Conferencesunmatched
  • Constraint Satisfactionunmatched
  • Data Modelingunmatched
  • Deep Learningunmatched
  • Develop Methodologiesunmatched
  • Experiment Designunmatched
  • Formal Verificationunmatched
  • Home Automationunmatched
  • Integer programmingunmatched
  • Javaunmatched
  • Machine Learningunmatched
  • Maintain Complianceunmatched
  • Mentoringunmatched
  • Model Reviewunmatched
  • Modeling Languagesunmatched
  • Network Configuration Managementunmatched
  • Neural Networksunmatched
  • Performance Managementunmatched
  • Policy Analysisunmatched
  • Procedure Developmentunmatched
  • Programming Languagesunmatched
  • Python Programming/Scripting Languageunmatched
  • Research Skillsunmatched
  • Resource Managementunmatched
  • Safety/Work Safetyunmatched
  • Scientific Researchunmatched
  • Search Engine Optimization (SEO)unmatched
  • Software Agentsunmatched
  • Software Engineeringunmatched
  • Static Analysisunmatched
  • Statistical Modelingunmatched
  • Statisticsunmatched
  • Systems Administration/Managementunmatched
  • Systems Reliabilityunmatched

Description

MULTIPLE POSITIONS AVAILABLE

Employer: AMAZON WEB SERVICES, INC.

Offered Position: Applied Scientist II

Job Location: Seattle, Washington

Job Number: AMZ9971140

Position Responsibilities:

Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Design and implement algorithms and formal methods for automated reasoning - including constraint solving, model checking, static analysis, and theorem proving - to verify the correctness, security, and reliability of cloud computing systems and generative AI applications. Develop new decision procedures, heuristics, and search strategies that improve the scalability and accuracy of verification tools. Build and deploy capabilities that enhance automated reasoning systems, such as learning-based heuristics for search and optimization, neural approaches to symbolic reasoning tasks, and data-driven techniques for abstraction and generalization. Extend and apply deep learning architectures (e.g., graph neural networks, transformers, recurrent models) and statistical modeling techniques (e.g., Bayesian inference, probabilistic programming) to problems in formal verification, program analysis, and code generation. Develop automated reasoning techniques for generative AI and agentic coding systems, including methods for verifying the correctness of AI-generated code, ensuring the safety and alignment of autonomous software agents, and applying formal guarantees to large language model (LLM) outputs. Design and build tools that combine symbolic reasoning with generative models to produce provably correct code and system configurations. Conduct original research at the intersection of machine learning and formal methods, including areas such as neuro-symbolic reasoning, program synthesis, interactive and automated theorem proving, abstract interpretation, scalable verification techniques, and formal methods for AI safety. Publish findings in peer-reviewed conferences and journals. Research and implement novel approaches combining ML with symbolic and logical reasoning to improve automated verification tools used across AWS services, including applications in access control policy analysis, network configuration verification, resource compliance checking, and system reliability assurance. Develop optimization methods - including linear and integer programming, convex optimization, and heuristic search - to solve constraint satisfaction, resource allocation, and scheduling problems arising in cloud computing and AI system development environments. Build and maintain production-grade automated reasoning tools and ML pipelines for AWS infrastructure. Design and execute experiments, analyze results using rigorous statistical methods, and iterate on model architectures and algorithmic strategies to improve performance at scale. Mentor junior engineers and scientists on formal methods, ML techniques, and best practices for building reliable automated reasoning systems.

Position Requirements:

Master"s degree or foreign equivalent degree in Computer Science, Machine Learning, Statistics, or a related field and one year of research or work experience in the job offered or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor"s degree or foreign equivalent degree in Computer Science, Machine Learning, Statistics, or a related field and five years of progressive post baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master"s degree and one year of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language.

Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.

40 hours / week, 8:00am-5:00pm, Salary Range $153,456/year to $193,200/year.

Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit:

https://www.aboutamazon.com/workplace/employee-benefits.#0000

Numbers & Facts

LocationSeattle, WA
IndustryRetail
Salary$153,456–$193,200 Per Year
Company Size10,000 employees or more
Year Founded1994
Websitehttp://Amazon.com/militaryroles

About Company

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

Similar Jobs

See more jobs