This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML & Forward Deployed Engineer based in Italy.
This role offers the opportunity to build and deploy high-impact AI, machine learning, and generative AI solutions from initial concept through production.
You will combine software engineering, machine learning, and MLOps/LLMOps expertise to create scalable and reliable AI products.
The position involves solving complex business problems through technologies such as LLMs, RAG pipelines, NLP, forecasting, and anomaly detection.
You will work across the full AI lifecycle, from experimentation and evaluation to deployment, monitoring, and continuous improvement.
Strong attention to security, governance, observability, and data quality will be essential when delivering production-ready solutions.
You will also collaborate closely with stakeholders to translate business needs into practical technical solutions and measurable outcomes.

This is an excellent opportunity for an experienced engineer who enjoys combining advanced AI technologies with hands-on implementation and real-world impact.
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Accountabilities
Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through production.
Build and optimize ML models and applications covering deep learning, NLP, forecasting, classification, regression, and anomaly detection use cases.
Develop production-grade GenAI applications using LLMs, RAG pipelines, embeddings, retrieval optimization, reranking, and prompt engineering.
Design and implement AI evaluation frameworks to assess model quality, reliability, relevance, and performance.
Build scalable AI services and integrations using REST and gRPC APIs as well as event-driven architectures.
Establish and maintain MLOps and LLMOps practices covering deployment, automation, versioning, monitoring, and lifecycle management.
Containerize and orchestrate AI applicat

AI/ML & Forward Deployed Engineer

Maestra

Bagnino

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