Applied Scientist, AICE - AI Center of Excellence
Amazon · Vancouver, Canada · Machine Learning Science
mid
machine learning
Applied Scientist
ic
· Posted Jun 24, 2026
C$149,300 – C$249,300
CAD per year
About this role
Amazon is hiring a mid-level Applied Scientist in the machine learning function based in Vancouver, Canada. The posting calls out experience with Python, Java, Machine Learning, A/B Testing. Compensation is listed at C$149,300–C$249,300 per year.
- Role
- Applied Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Vancouver, Canada
- Department
- Machine Learning Science
- Posted
- Jun 24, 2026
AI Summary
Applied Scientist at Amazon's AI Center of Excellence develops AI/ML primitives for enterprise intelligence. Designs rigorous experiments, translates research into production-ready solutions, and collaborates with product teams to validate performance and drive AI transformation across the organization.
Job description
from Amazon careersThe AI Center of Excellence (AICE) builds AI primitives that power system-intrinsic intelligence and Trusted Intelligent Knowledge Infrastructure for both AI-as-a-Consumer and human users. We develop AI capabilities independently and in partnership with product-owning teams to evolve Amazon's AI-driven operations and productivity. Our impact is enterprise-broad and global.
We are looking for an Applied Scientist who can identify high-impact problems, design rigorous experiments, and translate research into hardened, reusable primitives ready for broad consumption across the enterprise.
Key job responsibilities
* Research, design, and develop AI/ML primitives - defining problem spaces, formulating approaches, running experiments, and validating outcomes with scientific rigor
* Translate research findings into production-ready primitives, working closely with machine learning engineers to harden and scale solutions
* Drive the scientific direction of AICE primitives, identifying opportunities where novel approaches can unlock step-function improvements
* Design and execute experiments to validate primitive performance, robustness, and generalizability before broad consumption by partner teams
* Collaborate with product-owning teams to understand their problem spaces and ensure AICE primitives deliver measurable value when integrated
* Contribute to AICE's mission of driving AI transformation through best practices in applied research, evaluation methodology, and responsible AI within your area of expertise
* Publish findings, share learnings, and raise the scientific bar across the team
A day in the life
Every day brings new challenges. You might be deep in experimentation - designing evaluations to stress-test a new primitive's robustness. The next day, you could be analyzing results and iterating on model architectures. Later in the week, you may collaborate with partners to understand their domain and shape a primitive that fits their product needs. Other days, you'll work alongside our MLEs to harden a validated approach for broader consumption.
No two weeks look the same. You'll move fluidly between research and applied problem-solving - always with the goal of building AI primitives that are scientifically sound, trusted, and impactful at enterprise scale.
About the team
AICE is a team of scientists and machine learning engineers building the AI primitives that power Amazon's intelligent systems. We develop and harden reusable capabilities for broad consumption by product teams across the enterprise - and partner with those teams to integrate them.
- Experience with programming languages such as Python, Java, C++
- Ability to work across the research-to-production spectrum - from formulating hypotheses to validating primitives in production environments
- Familiarity with traditional software development practices with the ability to also leverage AI-assisted development tools effectively
- Experience designing and running experiments, A/B tests, or rigorous offline evaluations
- Track record of translating research into applied solutions that operate at scale
- Strong foundation in statistical methods, experimental design, and model evaluation
- Experience building reusable ML/AI components, frameworks, or primitives consumed by other teams
- Experience in information retrieval, knowledge representation, or agentic AI systems
- Demonstrated ability to collaborate with engineering teams to harden research prototypes for production
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
CAN, BC, Vancouver - 149,300.00 - 249,300.00 CAD annually
We are looking for an Applied Scientist who can identify high-impact problems, design rigorous experiments, and translate research into hardened, reusable primitives ready for broad consumption across the enterprise.
Key job responsibilities
* Research, design, and develop AI/ML primitives - defining problem spaces, formulating approaches, running experiments, and validating outcomes with scientific rigor
* Translate research findings into production-ready primitives, working closely with machine learning engineers to harden and scale solutions
* Drive the scientific direction of AICE primitives, identifying opportunities where novel approaches can unlock step-function improvements
* Design and execute experiments to validate primitive performance, robustness, and generalizability before broad consumption by partner teams
* Collaborate with product-owning teams to understand their problem spaces and ensure AICE primitives deliver measurable value when integrated
* Contribute to AICE's mission of driving AI transformation through best practices in applied research, evaluation methodology, and responsible AI within your area of expertise
* Publish findings, share learnings, and raise the scientific bar across the team
A day in the life
Every day brings new challenges. You might be deep in experimentation - designing evaluations to stress-test a new primitive's robustness. The next day, you could be analyzing results and iterating on model architectures. Later in the week, you may collaborate with partners to understand their domain and shape a primitive that fits their product needs. Other days, you'll work alongside our MLEs to harden a validated approach for broader consumption.
No two weeks look the same. You'll move fluidly between research and applied problem-solving - always with the goal of building AI primitives that are scientifically sound, trusted, and impactful at enterprise scale.
About the team
AICE is a team of scientists and machine learning engineers building the AI primitives that power Amazon's intelligent systems. We develop and harden reusable capabilities for broad consumption by product teams across the enterprise - and partner with those teams to integrate them.
Basic Qualifications
- PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)- Experience with programming languages such as Python, Java, C++
- Ability to work across the research-to-production spectrum - from formulating hypotheses to validating primitives in production environments
- Familiarity with traditional software development practices with the ability to also leverage AI-assisted development tools effectively
- Experience designing and running experiments, A/B tests, or rigorous offline evaluations
- Track record of translating research into applied solutions that operate at scale
- Strong foundation in statistical methods, experimental design, and model evaluation
Preferred Qualifications
- Experience in patents or publications at top-tier peer-reviewed conferences or journals- Experience building reusable ML/AI components, frameworks, or primitives consumed by other teams
- Experience in information retrieval, knowledge representation, or agentic AI systems
- Demonstrated ability to collaborate with engineering teams to harden research prototypes for production
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, BC, Vancouver - 149,300.00 - 249,300.00 CAD annually
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