Senior Applied Scientist, Supply Chain Ai Automation

5+ years of hands-on experience in applied machine learning, including building and deploying models in production.

Strong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow).

Proven track record of delivering business value through ML solutions in production environments.

Experience with end-to-end ML lifecycle, from research/prototyping to deployment at scale.

Demonstrated ability to identify high-impact ML opportunities and deliver measurable outcomes.

Strong problem-solving and coding skills.

Excellent communication skills, both technical and non-technical.

Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or a related field.

About the Team:
We're a newly formed elite team at Amazon with a bold mission: to revolutionize supply chain automation through state-of-the-art AI technology. Our charter is to leverage emerging technologies, particularly Agentic AI, to create autonomous systems that will transform how Amazon's global supply chain operates.

The Opportunity:
We're reimagining supply chain automation from the ground up. By combining state-of-the-art AI techniques with emerging Agentic AI capabilities, we're building autonomous systems that can understand, reason about, and optimize complex supply chain operations. Our goal is to create AI agents that can independently handle complex decision-making processes, dramatically reducing operational costs and improving efficiency across Amazon's global network.

This isn't just about implementing existing solutions – it's about pioneering new approaches to automation that will set industry standards for years to come. You'll be working at the intersection of:

• Cutting-edge AI/ML technologies
• Large-scale automation systems
• Complex supply chain operations
• Autonomous decision-making agents

Required Experience:
Proven track record of delivering significant business value through ML solutions in production environments.
5+ years of hands-on experience in applied machine learning.
Strong history of end-to-end ML implementation, from concept to production at scale.
Expertise in Python and modern ML frameworks (PyTorch, TensorFlow).
Demonstrated ability to identify high-impact opportunities and deliver measurable results.

What Sets Great Candidates Apart:
Experience with or strong interest in emerging AI technologies, including Agentic AI and LLMs.
Knowledge of software engineering best practices and agile development methodologies.
Familiarity with supply chain operations or large-scale logistics.
Experience with AWS services and cloud-based ML deployments.
Advanced degree in Computer Science, ML, or related field.

Why This Role Matters:
This isn't just another ML position. You'll be part of an elite team tasked with pushing the boundaries of what's possible with AI at Amazon's scale. Your work will directly impact millions of customers and has the potential to transform how we operate globally. By creating autonomous systems that can optimize our supply chain, you'll be at the forefront of a technological revolution in logistics and operations.

What We're Looking For in You:
Bias for action and ability to move fast while maintaining high standards.
Track record of turning complex problems into elegant, scalable solutions.
Strong business acumen and ability to identify high-impact automation opportunities.
Excellence in communication with both technical and business stakeholders.
Passion for learning and adapting to emerging technologies like Agentic AI

Key job responsibilities

• Lead the development of innovative ML and AI solutions for supply chain automation
• Rapidly prototype and validate new ideas through minimum lovable products (MLPs)
• Transform promising prototypes into production-ready systems at global scale
• Collaborate with business stakeholders to identify and prioritize high-value automation opportunities
• Mentor team members and promote engineering excellence in AI/ML practices

About the team
We work back to back to address the technical challenges of automation across a variety of products, software, and systems. Our scientists and machine learning engineers work in synergy to solve hard problems and enrich each other's skills. Together, we are a powerful team of worldwide specialists in bringing the potential of practical ML and AI to the max with impact on millions of Amazon customers.

Experience with or deep interest in Agentic AI, LLMs, or emerging AI technologies.

Hands-on experience designing autonomous decision-making systems.

Exposure to Amazon-scale systems or large-scale distributed ML systems.

Prior experience with supply chain, logistics, or operations research problems.

Proficiency with AWS services, especially for cloud-based ML deployment.

Understanding of software engineering best practices and agile methodologies.

Experience mentoring others and promoting ML/engineering excellence.

Ph.D. in ML, AI, or related quantitative discipline is a strong plus.

Demonstrated ownership and ability to deliver results in ambiguous and fast-paced environments.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.