AI/ML Systems Engineer: Deep Learning & Gen AI

Accenture Italia; Lombardia; On-site; EUR 32,000 - 66,000; Full time

Job summary

Accenture Italia seeks an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients in Lombardy, blending custom models with cloud services to deliver production-ready outcomes across the full solution lifecycle.

You will work with Deep Learning, Generative AI, and Large Language Models, design scalable data and MLOps pipelines, and ensure quality and value of deployed systems while partnering with business, engineering, and design teams on

Qualifications

• Bachelor's degree or equivalent required.
• Proven experience deploying AI/ML models in production at scale and monitoring.
• Experience with distributed computing, cloud deployment, and data pipelines.

Responsibilities

• Formulate real-world problems into scalable AI/ML solutions.
• Develop and implement ML algorithms, models, and scalable data pipelines with MLOps.
• Customize Deep Learning and Gen AI models for business needs and data availability.
• Engage in R&D of AI algorithms and simulations for client use cases.
• Work with large-scale datasets and perform data preprocessing for training and production.
• Implement and maintain data storage/retrieval mechanisms for models and knowledge.
• Justify model choices to business stakeholders.
• Collaborate with cross-functional teams across business and tech sides.

Skills

Machine learning engineer

Distributed computing

Python

C++

Java

R

SQL

Communication

Client-facing

Education

Bachelor's degree or equivalent

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Spark

Job description

Accenture Italia seeks an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients in Lombardy, blending custom models with cloud services to deliver production-ready outcomes across the full solution lifecycle.

You will work with Deep Learning, Generative AI, and Large Language Models, design scalable data and MLOps pipelines, and ensure quality and value of deployed systems while partnering with business, engineering, and design teams on