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Software Development Engineer, Amazon Freight Pricing

职能工程
级别中级
地点Vancouver, BC, CAN
方式现场办公
类型全职
发布2周前
立即申请

Amazon Freight (AF) is transforming the multi-billion-dollar trucking industry by building technology that enables external customers to access the scale, reliability, and innovation of Amazon’s logistics network.

Pricing is central to Amazon Freight’s growth and profitability. Every contract bid and on-demand quote directly impacts revenue, margin performance, and long-term portfolio health. The Amazon Freight Pricing team owns the intelligent systems that generate data-driven prices for both contract and spot freight across TL, LTL and Rail offerings.

We are building an AI-first pricing platform - where machine learning models, data-driven experimentation, and automated decision support are embedded directly into production systems and sales workflows. Our goal is not just to generate prices, but to continuously learn, adapt, and improve pricing accuracy and margin performance over time.

As an SDE II on the Amazon Freight Pricing team, you will build and scale the platforms that power:

  • ML-driven cost and price prediction
  • Margin modeling and scenario analysis
  • Contract pricing workflows and sales tooling
  • Real-time on-demand (spot) pricing systems
  • Monitoring, feedback loops, and model performance evaluation
    Our systems ingest large volumes of transportation, operational, and financial data to produce reliable price recommendations and insights. We partner closely with Research Science teams to productionize ML models and evolve them through continuous experimentation and performance tracking.

In this role, you will:

  • Design and build scalable backend services that power contract and spot pricing
  • Integrate ML models into resilient, observable production systems
  • Develop infrastructure to support model deployment, monitoring, and iteration
  • Build LLM driven intelligent tooling that augments business decision-making with data-driven insights
  • Improve system reliability, latency, and cost efficiency at scale
  • Collaborate across engineering, product, research science, and business stakeholders globally
    Prior ML experience is not required; engineers will gain hands-on experience integrating and operating ML-enabled services in production.

This role is ideal for engineers who want to work on high-impact systems where AI and large-scale distributed systems intersect to directly influence revenue and profitability. You will solve complex problems at the intersection of backend engineering, data systems, and applied machine learning — while helping shape the next generation of pricing intelligence at Amazon Freight.

  • Key job responsibilities
  • Design and build scalable backend services for contract and spot pricing systems.
  • Own end-to-end delivery of features from design through production support.
  • Integrate and operate ML models within reliable, observable production systems.
  • Develop APIs and internal tools that support sales and business decision-making.
  • Improve system performance, scalability, and operational excellence.
  • Participate in team on-call rotations, driving operational excellence through monitoring, incident response, and root cause resolution.

Basic Qualifications

  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language

Preferred Qualifications

  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent

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 - 114,800.00 - 191,800.00 CAD annually

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关于Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

10条评价

3.4

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.0

职业发展

3.8

管理层

2.7

65%

推荐率

优点

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

缺点

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

薪资范围

4个数据点

L2

L6

L3

L4

L5

L2 · Data Analyst L2

0份报告

$108,330

年薪总额

基本工资

$43,332

股票

$54,165

奖金

$10,833

$75,831

$140,829

面试评价

6条评价

难度

4.0

/ 5

时长

21-35周

体验

正面 0%

中性 17%

负面 83%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge