Senior Applied Scientist, Industrial Robotics Group
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Job Location:
Seattle, OR - USA
Monthly Salary:
Not Disclosed
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Amazon Industrial Robotics is seeking exceptional applied science talent to develop AI and machine learning systems that will enable the next generation of advanced manufacturing capabilities at unprecedented scale. Were building revolutionary software infrastructure that combines cutting-edge AI large-scale optimization and advanced manufacturing processes to create adaptive production control systems.
As a Senior Applied Scientist you will develop and improve machine learning systems that enable real-time manufacturing flow decisions. You will leverage state-of-the-art optimization and ML techniques evaluate them against representative manufacturing scenarios and adapt them to meet the robustness reliability and performance needs of production environments. You will invent new algorithms where gaps exist. Youll collaborate closely with software engineering manufacturing engineering robotics simulation and operations teams and your outputs will directly power the systems that determine what to build next where to allocate resources and how to maximize throughput.
The ideal candidate brings deep expertise in optimization and machine learning with a proven track record of delivering scientifically complex solutions into production. You are hands-on writing significant portions of critical-path scientific code while driving your teams scientific agenda. If youre passionate about inventing the intelligent manufacturing systems of tomorrow rather than optimizing those of today this role offers the chance to make a lasting impact on the future of automation.
Key job responsibilities
- Identify and devise new scientific approaches for constraint identification dispatch optimization WIP release control and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented
- Lead the design implementation and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production
- Design and build ML models and optimization algorithms including constraint prediction starvation risk forecasting and dispatch optimization
- Write a significant portion of critical-path scientific code with solutions that are inventive maintainable scalable and extensible
- Execute rapid rigorous experimentation with reproducible results closing the gap between simulation and real manufacturing environments
- Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone
- Influence your teams science and business strategy through insightful contributions to roadmaps goals and priorities
- Partner with manufacturing engineering robotics simulation and applied intelligence teams to ensure scientific approaches are grounded in operational reality
- Drive your teams scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations
- Actively participate in hiring and mentor other scientists improving their skills and ability to deliver
- Write clear narratives and documentation describing scientific solutions and design choices
- Knowledge of programming languages such as C/C Python Java or Perl
- PhD in computer science operations research machine learning industrial engineering or a related quantitative field or Masters degree plus 4 years building ML models and algorithms in applied settings
- 5 years of experience applying machine learning optimization or decision systems to complex real-world problems
- Proven track record of delivering scientifically complex solutions into production
- Deep expertise in one or more of: combinatorial optimization reinforcement learning constraint programming or stochastic modeling
- Ability to design rigorous experiments analyze results and iterate quickly with reproducible baselines
- Demonstrated technical contributions through publications patents or impactful production systems
- 8 years of experience in applied science or research with progressive scope and impact
- Experience with manufacturing systems production scheduling supply chain optimization or industrial process control
- Experience with Theory of Constraints or flow-based production optimization
- Experience with real-time decision systems that operate under uncertainty
- Experience with sim-to-real transfer or physics-informed machine learning
- Experience with AWS services including SageMaker and familiarity with MLOps practices
- Experience with AI-native development practices and AI coding assistants
- Knowledge of manufacturing execution systems (MES) SCADA ERP or related industrial software
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.
As a Senior Applied Scientist you will develop and improve machine learning systems that enable real-time manufacturing flow decisions. You will leverage state-of-the-art optimization and ML techniques evaluate them against representative manufacturing scenarios and adapt them to meet the robustness reliability and performance needs of production environments. You will invent new algorithms where gaps exist. Youll collaborate closely with software engineering manufacturing engineering robotics simulation and operations teams and your outputs will directly power the systems that determine what to build next where to allocate resources and how to maximize throughput.
The ideal candidate brings deep expertise in optimization and machine learning with a proven track record of delivering scientifically complex solutions into production. You are hands-on writing significant portions of critical-path scientific code while driving your teams scientific agenda. If youre passionate about inventing the intelligent manufacturing systems of tomorrow rather than optimizing those of today this role offers the chance to make a lasting impact on the future of automation.
Key job responsibilities
- Identify and devise new scientific approaches for constraint identification dispatch optimization WIP release control and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented
- Lead the design implementation and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production
- Design and build ML models and optimization algorithms including constraint prediction starvation risk forecasting and dispatch optimization
- Write a significant portion of critical-path scientific code with solutions that are inventive maintainable scalable and extensible
- Execute rapid rigorous experimentation with reproducible results closing the gap between simulation and real manufacturing environments
- Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone
- Influence your teams science and business strategy through insightful contributions to roadmaps goals and priorities
- Partner with manufacturing engineering robotics simulation and applied intelligence teams to ensure scientific approaches are grounded in operational reality
- Drive your teams scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations
- Actively participate in hiring and mentor other scientists improving their skills and ability to deliver
- Write clear narratives and documentation describing scientific solutions and design choices
- Knowledge of programming languages such as C/C Python Java or Perl
- PhD in computer science operations research machine learning industrial engineering or a related quantitative field or Masters degree plus 4 years building ML models and algorithms in applied settings
- 5 years of experience applying machine learning optimization or decision systems to complex real-world problems
- Proven track record of delivering scientifically complex solutions into production
- Deep expertise in one or more of: combinatorial optimization reinforcement learning constraint programming or stochastic modeling
- Ability to design rigorous experiments analyze results and iterate quickly with reproducible baselines
- Demonstrated technical contributions through publications patents or impactful production systems
- 8 years of experience in applied science or research with progressive scope and impact
- Experience with manufacturing systems production scheduling supply chain optimization or industrial process control
- Experience with Theory of Constraints or flow-based production optimization
- Experience with real-time decision systems that operate under uncertainty
- Experience with sim-to-real transfer or physics-informed machine learning
- Experience with AWS services including SageMaker and familiarity with MLOps practices
- Experience with AI-native development practices and AI coding assistants
- Knowledge of manufacturing execution systems (MES) SCADA ERP or related industrial software
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
Key Skills
About Company
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