Applied Scientist, AI Ops Integration

Amazon; Dublin; On-site; EUR 150,000 - 190,000; Full time

Job summary

Amazon seeks an Applied Scientist to fuse state-of-the-art ML/AI with autonomous AI capabilities to optimize complex supply chain operations. You will build autonomous systems that understand, reason about, and improve decisions across Amazon's global operations and logistics.

In this role you will prototype ideas into production-scale solutions, collaborate with stakeholders to prioritize high-value automation, and mentor junior engineers while upholding engineering excellence in AI/ML

Qualifications

• PhD or Master's degree in CS, CE or ML or related field.
• Experience in building models for business applications.
• Experience in patents or publications at top-tier conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

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

Skills

ML/AI modeling

Production-scale systems

Problem solving

Team mentorship

Education

PhD or MS in CS/CE/ML

Tools

Java

C++

Python

Job description

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.

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