Applied Scientist, AI Ops Integration
Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Jul 22, 2026. Amazon scores B on the Alion truth index.
As part of AI Ops Integration team 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 an Applied Scientist you will combine state-of-the-art ML/AI techniques with emerging Agentic AI capabilities to build autonomous systems that can understand, reason about, and optimize complex supply chain operations. You will also have the opportunity to work on CV and other relevant technologies.
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
- Lead the development of innovative ML and AI solutions for supply chain and operations
- 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 junior members and promote engineering excellence in AI/ML practices
About the team
We work back to back to address the technical challenges of automation and intelligence 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 team of worldwide specialists in bringing the potential of practical ML and AI to the max with impact on millions of Amazon customers.
Basic qualifications
- PhD, or a Master's degree and experience in CS, CE, ML or related field
- Experience in building models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred qualifications
- Experience in professional software development
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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.