Applied Scientist, AI Ops Integration

Amazon Science; Dublin; On-site; EUR 110,000 - 140,000; Full time

Job summary

Amazon Science is seeking an Applied Scientist to join the AI Ops Integration team in Ireland. You will combine state-of-the-art ML/AI techniques with emerging agentic AI capabilities to build autonomous systems for optimizing complex supply chain operations.

You will research open source and internal tools, handle highly ambiguous problems, and influence how Amazon Operations leverages AI at scale. A startup-like mindset within the scale of Amazon applies.

Qualifications

• PhD, or a Master’s degree with strong ML/AI background.
• Experience building models for business applications and ML workflows.
• Publications or patents in top-tier venues are preferred.

Responsibilities

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

Skills

Machine Learning

Java

C++

Python

Distributed computing

Research publications

Education

PhD or Master’s in CS/CE/ML

Tools

scikit-learn

TensorFlow

Spark

MxNet

Hadoop

Job description

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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