Amazon EU SARL, Irish Branch
Technology
SeniorMachineLearningSoftwareDevelopmentEngineer,AIOpsIntegration
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“Senior Machine Learning Software Development Engineer, AI Ops Integration at Amazon EU SARL, Irish Branch. Skills: Machine Learning, AI Ops, LLM, Agentic AI. Lead technical design of ML/LLM systems. Architect agentic AI solutions”
What You'll Achieve.
Automate decision-making; Process real decisions daily
Industry & Context.
Solve operational challenges; Tackle ambiguous problems; Reasoning; Problem-solving
What They're Looking For.
Must Have
Bachelor's degree, Experience as a mentor, Experience leading an engineering team, Experience in professional software development, Experience leading architecture and design, Experience programming with Java, C++, or C#, Knowledge of machine learning concepts
Nice to Have
Master's degree in computer science, Experience with full software development lifecycle, Experience with Machine Learning fundamentals, Experience with Large Language Model fundamentals, Experience with vLLM, SGLang, TensorRT, Experience in machine learning, Experience in statistics, Experience in deep learning, Experience in natural language processing, Experience in information retrieval, Experience with feature delivery, Experience with operations/supply chain, Experience researching machine learning, Experience researching deep learning, Experience researching NLP, Experience researching computer vision, Experience researching data science, Experience communicating across technical audiences, Experience communicating across non-technical audiences, Experience communicating with executive stakeholders, Experience using data and metrics
What You'll Do.
Lead technical design of ML/LLM systems
Architect agentic AI solutions
Build agentic AI solutions
Orchestrate operational workflows
Define technical strategy for tooling
Design front-end platforms
Serve non-technical users
Own integration architecture
Establish modular orchestration patterns
Drive engineering excellence
Set standards for experimentation
Set standards for deployment
Set standards for monitoring
Set standards for evaluation
Set standards for incident response
Design guardrails for AI systems
Design evaluation frameworks
Design human-in-the-loop architectures
Ensure AI systems operate safely
Ensure AI systems operate reliably
Mentor junior engineers
Conduct design reviews
Partner with scientists
Partner with product managers
Partner with operations leaders
Translate business problems into solutions
How You'll Work.
Team & Collaboration
Cross-functional team; Operations partners; Scientists; Product managers; Operations leaders
Communication Scope
Executive presentations
Process & Methodology
Technical strategy, Delivery milestones
Full Job Description
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, eval
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