As part of AI Operations Integration, we have a vision to transform Amazon Operations & Supply Chain into an AI-Native organization by delivering intuitive and differentiated AI solutions that solve enduring operational challenges. We blend vision with curiosity and Amazon's real-world experience to build rapidly AI capabilities. We accelerate our customers' businesses: internal operations teams across Amazon's global footprint through delivery of predictive analytics, LLMs and autonomous AI agents to automate decision-making across Amazon's global operations and supply chain.
As a Machine Learning Software Development Engineer, you'll design and deploy production ready systems that combine traditional ML with modern agentic architectures to solve impactful operational problems at scale.
This role combines the excitement of a startup environment with the scale of Amazon Operations. You'll research state-of-the-art open source and internal tools and will tackle highly ambiguous problems. If you thrive on ownership and dealing with ambiguity, passionate about AI and want to fundamentally influence how Amazon Operations leverages AI, this role offers an extraordinary opportunity to make your mark.
Key job responsibilities
What you'll do:
- Lead the technical design and architecture of production ML/LLM systems end-to-end from data pipelines and model serving to scalable user-facing applications
- Architect and build agentic AI solutions that orchestrate complex operational workflows across multiple systems, APIs, and decision points
- Define the technical strategy for internal tooling. Designing front-end platforms (dashboards, products) that serve non-technical operations users at worldwide scale
- Own the integration architecture across internal systems, databases, and MCP servers: establishing patterns that enable modular multi-system orchestration
- Drive engineering excellence across the ML lifecycle: set standards for experimentation, deployment, monitoring, evaluation, and incident response
- Design guardrails, evaluation frameworks, and human-in-the-loop architectures that ensure production AI systems operate safely and reliably at scale
- Mentor junior engineers, conduct design reviews, and raise the technical bar across the team
- Partner with scientists, product managers, and operations leaders to translate ambiguous business problems into well-scoped technical solutions with clear delivery milestones
About the team
We're a cross-functional team of machine learning engineers, ML & AI scientists and Technical PM focused on automating operational decisions in Amazon's supply chain.
Our charter is to identify high-impact automation opportunities, build AI agents that can handle them reliably, and deploy these systems into production
where they process real decisions daily.
The team operates with a build-measure-learn cycle. We work closely with operations partners to understand their problems, prototype solutions quickly, measure impact rigorously, and iterate based on real-world performance.
- Bachelor's degree
- Experience as a mentor, tech lead or leading an engineering team
- Experience in professional, non-internship software development
- Experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience building complex software systems that have been successfully delivered to customers
- Master's degree in computer science or equivalent
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience with vLLM, SGLang, TensorRT or similar platforms in production environments
- Experience in several of the following areas: machine learning, statistics, deep learning, natural language processing, or information retrieval
- Experience with feature delivery and tradeoffs of a product
- Experience with operations/supply chain
- Experience researching about machine learning, deep learning, NLP, computer vision, data science
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience using data and metrics to measure impact and determine improvements
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.
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.
