AI/ML Engineer

E.ON Drive Infrastructure Italy S.r.l; United States; Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid working with flexible hours

Workation: EU abroad allowed

Training budget 5000 EUR/year

Welcome gifts & hardware provided

Job summary

E.ON Drive Infrastructure Italy S.r.l is seeking a Senior AI/ML Engineer to design, build, and scale production AI systems across a pan-European network. You will own solutions from experimentation to deployment and help shape the AI UNIT's technical foundation.

Responsibilities include MLOps, LLMOps, RAG, agents, and evaluating new models and tooling while collaborating with data scientists and engineers. Hybrid work, competitive salary, and a 5,000 euro annual training budget are offered.

Qualifications

• Proven experience deploying AI/ML solutions in production end-to-end.
• Strong software engineering fundamentals and Python expertise.
• Experience with GenAI, RAG, agents, and evaluation frameworks.

Responsibilities

• Design, build and operate production-grade AI/ML systems with reliability, latency and cost in mind.
• Own ML models from experimentation to production and monitor performance.
• Define and improve MLOps and LLMOps practices and logging.

Skills

Python

MLOps

LLMOps

AI/ML architectures

GenAI & prompting

Production deployment

Tools

Azure

AWS

GCP

CI/CD

Docker

Job description

Задачи

Most AI lives in a chat window. Ours will run physical infrastructure across a pan-European network. As a Senior AI/ML Engineer in our newly established AI UNIT within E.ON Drive Infrastructure (EDRI), a special unit built and run like a startup, you will be at the forefront of designing, building, and scaling AI systems that deliver real business impact. Working across the entire AI lifecycle, you will take solutions from experimentation to production and own them there, while helping define the technical foundation of our AI UNIT. You report to our Head of AI Strategy. Shape the AI/ML architecture, technology stack, and engineering standards of the unit. Design, build, and operate production-grade AI and machine learning systems and own their reliability, quality, latency, and cost. Develop classical ML and GenAI solutions, including RAG, agentic systems, and AI-powered services. Productionize ML models developed by our Data Scientists and operate them at scale. Define and enhance MLOps and LLMOps practices for deployment, versioning, monitoring, evaluation, and retraining. Own our LLM gateway, including model routing, token limits, cost per use case, guardrails, and logging. Build scalable AI services and APIs for our Full-Stack and AI Deployment Engineers. Evaluate emerging AI models, AI tooling, and agentic systems and integrate impactful innovations into our stack. Share knowledge and support the growth of junior colleagues – this is a senior individual contributor role.

Требования

You are an experienced AI engineer who combines strong software engineering fundamentals with hands-on expertise in modern machine learning and Generative AI. You enjoy solving complex problems, taking ownership, and turning ideas into production-ready solutions. Proven experience owning AI/ML solutions in production end to end, with measurable impact. Strong software engineering skills in Python, including testing, CI/CD, and clean architecture. Solid understanding of machine learning concepts, model evaluation, and experimentation. Production experience with Generative AI, including prompting, RAG, agents, and evaluation frameworks. Experience with MLOps and model deployment workflows in Azure - AWS or GCP experience transfers. Strong understanding of trade-offs between accuracy, latency, scalability, cost, and risk. Ability to translate complex business and technical challenges into practical solutions. Curious, pragmatic, and passionate about applying the latest AI technologies to real-world problems. Strong communication skills and the ability to collaborate effectively across technical and non-technical teams. Fine-tuning, post-training, or inference optimization. Optimization or operations research. Experience with physical infrastructure, energy, mobility, or other asset-heavy industries. Open-source contributions or public work – side projects count.

Условия

• Hybrid working with flexible working hours.
• Workation: Enjoy the flexibility to work temporarily from abroad - within the EU.
• You will receive a competitive salary.
• A company pension scheme is of course also one of the benefits with us.
• Sustainable learning opportunities: We support you with a training budget of 5,000 euros per year.
• You get everything you need to get started: onboarding with welcome gifts and all the hardware you need.
• Contact Diversity counts at E.ON.
• We welcome all people and are convinced that differences make us stronger.
• Become part of our inclusive and diverse corporate culture!