AI/ML Solutions Architect Manager

Accenture Italia

Roma

On-site

EUR 60,000 - 90,000

Full time

14 days+
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Job summary

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.

Qualifications

  • 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.

Responsibilities

  • 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.

Skills

Machine Learning
Python
Cloud computing
MLOps/LLMOps
Deep Learning
Gen AI
LLMs
PyTorch
TensorFlow
Data Pipelines

Education

Bachelor's Degree or equivalent

Tools

Docker
Kubernetes
Terraform
Spark
SQL
Linux

Job description

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.

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