Deep AI native software engineer

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

YOU ARE

As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.

YOU ARE

As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.

THE WORK

• Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions
• Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps
• Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC
• Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites
• Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production
• Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools
• Justify the value of model approaches in business problems
• Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production

EDUCATION

• Bachelor's Degree or equivalent

Basic (required) Qualification

• Proven experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.
• Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering and programming
• Hands-on experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks
• Experience in building and deploying AI/ML based software to a cloud environment.

Preferred Qualification

• Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..
• Experience working with language models like LLM's APIs and optimizing their usage for specific applications.
• Experience with the following programming languages: Python, C++, Java, R, SQL
• Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders
• Strong client-facing skillsets in a consulting environment
• Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams
• Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation
• MS or PhD in related field preferred (computer science, engineering, etc.)

Compensation at Accenture varies depending on a wide array of factors including but not limited to role, level, seniority, responsibility, skillset, and level of experience. For this position, the Metalmeccanico National Collective Bargaining Agreement applies, with one of the following pay grades and corresponding gross annual salary range:

• B2- €32,000 - €50,500
• B3- €36,000 - €65,800