Applied Scientist II ML/AI

Amazon; Vancouver; On-site; CAD 100,000 - 140,000; Full time

Job summary

A global technology company in Metro Vancouver is seeking an Applied Scientist II to develop and implement machine learning solutions that optimize fulfillment processes. The ideal candidate will have a strong background in machine learning, data mining, and algorithms. Responsibilities include designing ML models, researching new techniques, and collaborating with engineering teams. This position offers a chance to impact billions of dollars in business across multiple markets, fostering a collaborative and innovative environment.

Benefits

Health insurance

Registered Retirement Savings Plan (RRSP)

Paid time off

Qualifications

• 3+ years of experience building models for business applications.
• Experience in algorithms and data structures, numerical optimization, and high-performance computing.
• Experience in state-of-the-art deep learning model architecture design.

Responsibilities

• Design, develop, and evaluate tailored ML/AI models for complex business problems.
• Research and apply the latest ML/AI techniques.
• Develop frameworks for evaluation and validation of AI agents.

Skills

Machine Learning Models

Generative AI solutions

Data Mining

Deep Learning

Algorithms

Education

PhD or Master’s degree in CS, CE, ML or related field

Tools

TensorFlow

MXNet

Unix/Linux

Job description

Applied Scientist II ML/AI, Fulfillment Planning and Execution Science – Fulfillment Optimization

Have you ever wondered how Amazon predicts delivery times and ensures your orders arrive exactly when promised? Have you wondered where all those Amazon semi‑trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon’s multimodal logistics network that includes planes, trucks, and vans sound exciting to you? Are you interested in developing Generative AI solutions using state‑of‑the‑art LLM techniques to revolutionize how Amazon optimizes the fulfillment of millions of customer orders globally with unprecedented scale and precision? If so, then we want to talk with you! Join our team to apply the latest advancements in Generative AI to enhance our capability and speed of decision making.

Key job responsibilities

• Design, develop, and evaluate tailored ML/AI models for solving complex business problems.
• Research and apply the latest ML/AI techniques and best practices from academia and industry.
• Identify and implement novel Generative AI use cases to deliver value.
• Design and implement Generative AI and LLM solutions to accelerate development and provide intuitive explainability of complex science models.
• Develop and implement frameworks for evaluation, validation, and benchmarking AI agents and LLM frameworks.
• Think about customers and how to improve the customer delivery experience.
• Use analytical techniques to create scalable solutions for business problems.
• Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at large scale.
• Establish scalable, efficient, automated processes for large‑scale data analyses, model development, model validation, and model implementation.

A day in the life

In this role, you will learn how Amazon plans for and executes within its logistics network, including Fulfillment Centers, Sort Centers, and Delivery Stations. You will design and develop Machine Learning/AI models with significant scope, impact, and high visibility. Your focus will be on designing, developing, and deploying Generative AI solutions at scale that improve efficiency, increase productivity, accelerate development, automate manual tasks, and deliver value to internal customers. Your solutions will impact business segments worth many billions of dollars across multiple countries and markets. From day one you will be working with bar‑raising scientists, engineers, and designers, and collaborating with the broader science community in Amazon to broaden the horizon of your work. Successful candidates thrive in fast‑paced environments that encourage collaborative and creative problem solving, can measure and estimate risks, constructively critique peer research, and align research focuses with Amazon’s strategic needs. We look for individuals who know how to deliver results and are eager to develop themselves, their colleagues, and their careers.

About the team

FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution to improve Amazon’s operational efficiency worldwide at a scale that is unique to Amazon. We own the long‑term and intermediate‑term planning of Amazon’s global fulfillment centers and transportation network, as well as the short‑term network planning and execution that determines the optimal flow of customer orders through Amazon’s fulfillment network. FPX Science is a group of scientists from diverse technical backgrounds—Machine Learning, Operations Research, Simulation—that collaborate closely with you on your projects. We directly support multiple functional areas across SCOT – Fulfillment Optimization and the research needs of the corresponding product and engineering teams, disambiguating complex supply‑chain problems and creating innovative data‑driven solutions at scale with a mix of science‑based techniques. We are incorporating the latest advances in Generative AI and LLM techniques in how we design, develop, enhance, and interpret the results of these science models.

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 in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.
• Experience building machine learning models or developing algorithms for business application.
• Experience in state‑of‑the‑art deep learning model architecture design, deep learning training and optimization, and model pruning.

Preferred Qualifications

• Experience using Unix/Linux.
• Experience in professional software development.
• Experience with popular deep learning frameworks such as MXNet and TensorFlow.

Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. We have an inclusive culture that 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, 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.

Posted: January 27, 2026 (Updated 3 days ago)