Machine Learning Engineer, NA Supply Chain Execution and Planning Science (EPS)

The NA AMZL Supply Chain organization leads the innovation of Amazon’s Last Mile. We are an Operations org that hires and manages associates to deliver packages next day and sub-same day.

Our key vision is to transform the online experience by enabling ultra-fast delivery at lower cost possible. We’re growing in scale and volume, by orders of magnitude.

The Execution and Planning Science (EPS) team sits within NA AMZL Supply Chain with the mission to build world-class automated Science-Tech products that enable ultra-fast delivery speeds for Amazon customers and job market opportunities for Amazon associates.

We are team of Scientists, Engineers and Tech leaders who invent and implement scalable algorithms for automated decision making in the Operations space.

At Amazon, we are constantly inventing and re-inventing to be the most associate-centric company in the world. To get there, we need exceptionally talented, bright, and driven people.

Amazon is one of the most recognizable brand names in the world and we distribute millions of products each year to our loyal customers.

You will develop Science-Tech solutions to craft business strategy and roadmap to enable some of Amazon’s biggest brands to delight millions of customers.

To succeed, we need senior technical leaders to forge a path into the future by building innovative, maintainable, and scalable systems.

We are looking for a Machine Learning Engineer (MLE) to host and develop ML prediction and Optimization models. We’re looking for Engineers and Architects capable of using ML, GenAI and Optimization techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

You will own building models for production, typically which will be inputs to Optimization and ML models. In this role you will closely partner with Applied Scientists, Data Engineers, Product Managers and Technical Program Managers to deliver and implement automated decision-making algorithms.

This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping / simulation, to implementation by working closely with colleagues in engineering, product management, operations, retail and finance.

Key job responsibilities

• Collaborate with ML scientists and engineers to Research, design and develop cutting-edge ML, Optimization and GenAI algorithms to address real-world challenges
• Work across customer engagement to understand what adoption patterns for ML, Optimization and GenAI are working and rapidly share them across teams and leadership
• Interact with customers directly to understand the business problem, help and aid them in implementation of ML, Optimization and GenAI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI
• Create and deliver reusable technical assets that help to accelerate the adoption of ML, Optimization and GenAI across NA Supply Chain
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to Product and Engineering teams to help define product direction.

BASIC QUALIFICATIONS

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team

PREFERRED QUALIFICATIONS

• 5+ 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
30+ days ago