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Applied Scientist, Sales AI

ID: 5361

Type: Full-time

Category: Others

Company Name: Amazon Development Centre Canada ULC

Location: CAN, ON, Toronto - Toronto - Canada

Salary: 149,300.00 - 249,300.00 CAD annually

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Job Description

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing team with an exciting AI-first charter and need your passion, innovative thinking, and creativity to help take our products to new heights.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We break fresh ground in product and technical innovations every day!

Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top Applied Science talent to help us build new, science-backed services that drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency.

As an Applied Scientist on the team, you will bring deep expertise in quantitative modeling techniques such as Sequential Recommender Systems, Deep Learning, Reinforcement Learning or Hidden Markov Models. You have the scientific and technical skills to build and refine models that can be implemented in production, and you leverage Natural Language Processing and Generative AI models to enhance their explainability. You will contribute to chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems. You are fluently able to leverage the latest Generative AI systems and services to accelerate and improve your work while maintaining high quality in your work outputs.

Key job responsibilities
Scientific Modeling
- Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business
- Lead the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects
- Run regular A/B experiments, gather data, and perform statistical analysis
- Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving
- Publish scientific findings in reports and papers that can be shared internally and externally
Product Development Support
- Partner with software engineering and product management teams to support product and service development, define success metrics and measurement approaches, and help drive adoption of innovative new features for our services.
- Lead requirements gathering sessions with product teams and business stakeholders
- Maintain scientific documentation and knowledge for product initiatives
Collaboration & Communication
- Work closely with software engineers to deliver end-to-end solutions into production
- Translate complex scientific findings into actionable business recommendations for stakeholders and senior management
- Provide clear, compelling reports and presentations on a regular basis with respect to your models and services
- Communicate with internal teams to showcase results and identify best practices.

About the team
Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.

Basic Qualifications

- 3+ years of 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

Preferred Qualifications

- Experience using Unix/Linux
- Experience in professional software development
- Deep understanding of modeling frameworks that support sequential decision making such as Hidden Markov Models, Sequential Recommender Systems and Reinforcement Learning

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, ON, Toronto - 149,300.00 - 249,300.00 CAD annually

Company Information

Company Name: Amazon Development Centre Canada ULC

Company Website: https://www.amazon.jobs/en/locations/canada

Company Address: CAN, BC, Vancouver

Amazon Development Centre Canada ULC is a Canadian legal entity and part of the global Amazon organization that houses software development, product engineering, research and related technical operations supporting Amazon’s consumer retail, cloud, devices, media and advertising businesses. As a development centre entity within Amazon’s corporate structure, it functions as an engineering and product delivery organization that employs software engineers, data scientists, machine learning specialists, product managers, designers, quality engineers and operations staff to design, build, test and operate software systems and services used by Amazon customers and internal business teams. The company’s core activities are centered on software and systems development across multiple technology domains. These activities typically include back-end and front-end application development, distributed systems engineering, cloud services work (including integration with Amazon Web Services), data engineering, analytics and machine learning model development, natural language processing work for voice services, computer vision R&D, infrastructure automation, security engineering and developer tooling. Teams operating under the development centre model commonly focus on delivering scalable services for retail commerce (catalog, search, recommendations, pricing, inventory and checkout), digital media (streaming and content delivery), consumer devices (software for Alexa-enabled products and IoT integrations), advertising technology (targeting, measurement and auction systems), and enterprise offerings (AWS features and management tools). The organisation also supports lifecycle activities for Amazon products and services, including product management, technical program management, continuous integration and continuous delivery (CI/CD) pipelines, site reliability engineering (SRE), monitoring and incident response, performance engineering, and operational support. Development centres play a role in prototyping new features, running experiments and A/B tests, and collaborating with global product teams to localize and adapt features for Canadian markets when appropriate. The teams frequently interface with cross-functional stakeholders—user experience researchers, UX designers, business analysts, legal and policy teams, and operations—to deliver end-to-end solutions aligning with Amazon’s product and customer experience goals. In terms of products and services, Amazon Development Centre Canada ULC does not sell consumer-facing products under its own brand; rather, it contributes engineering and product work to Amazon’s broad portfolio. Outputs from its teams feed into Amazon’s retail platforms (amazon.ca and global retail storefronts), AWS services, Alexa and Echo device software, Prime Video and digital content systems, Amazon Logistics and fulfillment technology, Amazon Advertising products, and other Amazon-owned services. These contributions include new features, performance and scale improvements, security and compliance implementations, localization for Canadian customers, and enhancements to data and machine-learning systems used for personalization, fraud detection, supply chain optimization and advertising. As a legal entity in Canada, Amazon Development Centre Canada ULC typically supports hiring and employment, payroll administration, workplace facilities and compliance with Canadian regulatory and labour requirements for Amazon’s engineering workforce in the country. The development centre model enables Amazon to maintain distributed engineering capacity outside its U.S. headquarters, providing both local product focus and integration into Amazon’s global engineering processes and technology stacks. Teams in such centres often collaborate closely with other Amazon engineering groups across North America, Europe and Asia, participating in shared codebases, microservice architectures, global release processes and Amazon-wide technical standards. Amazon’s publicly stated corporate mission—to be Earth’s most customer-centric company—is reflected in the development centre’s emphasis on customer-focused product delivery, data-driven decision-making and rapid iteration. The centre’s efforts are typically aligned to measurable customer outcomes such as lower latency, more relevant search results and recommendations, improved reliability and availability of services, faster feature delivery, and localized enhancements that improve the experience for Canadian customers. The operation also invests in workforce development, supporting internships, university hiring pipelines, co-op programs and community engagement in the technology ecosystem, as part of Amazon’s broader commitments to hiring and local economic participation. Security, privacy and regulatory compliance are also core considerations for engineering work done by Amazon Development Centre Canada ULC. Teams are expected to follow Amazon-wide security practices, data protection standards and compliance programs to meet applicable Canadian and international legal requirements, particularly for customer data, payment processing and cloud services. Research and engineering efforts may include building privacy-preserving machine learning, secure authentication systems, and compliance tooling to support regulated industries and jurisdictional requirements. Overall, Amazon Development Centre Canada ULC operates as a technology-focused subsidiary entity within the Amazon corporate family, delivering software engineering, data science and product development work that underpins many of Amazon’s consumer and enterprise offerings. Its contributions enable Amazon to scale technology development globally while retaining localized capabilities for the Canadian market.
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