AI/ML Solutions Architect Manager

Accenture Italia; Roma; In loco; EUR 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

Accenture Italia is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI/ML solutions. You will develop scalable pipelines, customize models (DL, Gen AI, LLMs), and ensure reliable deployment across cloud environments and production systems.

Responsibilities include translating business problems into AI-ready solutions, building data pipelines with MLOps, and collaborating with cross-functional teams to deliver value at scale.

Competenze

• Bachelor's Degree or equivalent in a relevant field.
• Proven experience deploying ML models to production at scale.
• Strong CS foundations including architecture, systems, and programming.
• Experience with distributed computing, big data, cloud, and HPC environments.
• Ability to build AI/ML software for cloud deployment.

Mansioni

• Formulate real-world problems into scalable AI/ML solutions.
• Develop and implement ML models and data pipelines for training and production with DevOps & MLOps.
• Customize DL and Gen AI models for business use cases across data availability and infrastructure constraints.
• Collaborate with client teams and stakeholders to deploy AI capabilities at scale.
• Work with large datasets and ensure high-quality data for training and production.

Conoscenze

Machine Learning

Python

Cloud computing

MLOps/LLMOps

Deep Learning

Gen AI

LLMs

PyTorch

TensorFlow

Data Pipelines

Formazione

Bachelor's Degree or equivalent

Strumenti

Docker

Kubernetes

Terraform

Spark

SQL

Linux

Descrizione del lavoro

Accenture Italia is seeking an AI/ML Computational Scientist to design, build, and operationalize enterprise AI/ML solutions. You will develop scalable pipelines, customize models (DL, Gen AI, LLMs), and ensure reliable deployment across cloud environments and production systems.

Responsibilities include translating business problems into AI-ready solutions, building data pipelines with MLOps, and collaborating with cross-functional teams to deliver value at scale.