AI Engineer — Build Scalable AI & LLMs

Hermes Corporate; Mantova; In loco; EUR 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

Hermes Corporate is seeking an AI/ML Engineer to design and deploy AI-driven solutions across business domains. You will build end-to-end pipelines, fine-tune LLMs, and implement scalable deployment strategies in production.

You'll collaborate with engineering and product teams, monitor performance, and stay ahead on AI advances, including quantization, pruning, and RAG techniques. A strong Python background and experience with PyTorch or TensorFlow are essential.

Competenze

• Bachelor’s in Computer Science or related field.
• 3+ years hands-on experience building and deploying AI/ML systems.
• Strong Python skills with PyTorch and/or TensorFlow.
• Experience with transformers and LLMs.
• Familiarity with model optimization (quantization, pruning, distillation).
• Solid grasp of MLOps and deployment workflows.
• Strong problem-solving skills and attention to detail.

Mansioni

• Design and deploy AI models for complex business problems.
• Fine-tune LLMs (e.g., LLaMA, Mistral, Falcon) for domain-specific tasks.
• Build and manage data pipelines for model training and inference.
• Develop scalable model deployment strategies in production environments.
• Collaborate with cross-functional teams to build AI-powered applications.
• Monitor model performance and optimize for accuracy and efficiency.
• Stay up to date with the latest in AI, LLMs, and model optimization.

Conoscenze

Python

PyTorch

TensorFlow

Transformers

LLMs

MLOps

Problem solving

Formazione

Bachelor’s in Computer Science or related field

Master’s degree in AI/ML

Strumenti

Docker

Kubernetes

Cloud ML platforms

Descrizione del lavoro

Hermes Corporate is seeking an AI/ML Engineer to design and deploy AI-driven solutions across business domains. You will build end-to-end pipelines, fine-tune LLMs, and implement scalable deployment strategies in production.

You'll collaborate with engineering and product teams, monitor performance, and stay ahead on AI advances, including quantization, pruning, and RAG techniques. A strong Python background and experience with PyTorch or TensorFlow are essential.