Deep AI Native Software Engineering

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

Descrizione del lavoro

Accenture Italia in Milano seeks an AI/ML Computational Scientist to design, build, and operationalize AI/ML solutions for enterprise clients. You will work across model selection, data processing, and DevOps/MLOps pipelines to deliver production-ready outcomes.

The role includes researching new AI algorithms, applying DL/Gen AI to business use cases, and collaborating with diverse teams to achieve end-to-end project goals at client sites.

Competenze

• Bachelor's degree in CS/CE/Data Science or related field.
• Experience deploying ML models in production, with monitoring and audits.
• Strong foundations in computer science concepts and system architecture.

Mansioni

• Formulate real-world problems into scalable AI and ML solutions.
• Develop ML models and data pipelines for training and production with DevOps & MLOps.
• Customize DL and Gen AI models for client needs, including edge devices and HPC.
• Engage in R&D of new AI algorithms and simulations for complex business problems at client sites.
• Process large-scale datasets and ensure high-quality inputs for training/production.
• Justify model approaches and collaborate with both business and technical teams.

Conoscenze

Machine learning engineering

Cloud & DevOps concepts

Communication with stakeholders

Research & experimentation

Edge computing knowledge

Formazione

Bachelor's Degree in Computer Science/Engineering/Data Science

Strumenti

TensorFlow

PyTorch

LLM APIs

C++

Java

SQL

Python

Descrizione del lavoro

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 in Computer Science, Computer Engineering, Data Science, or a related field

Basic (required) Qualification

• Work or coursework experience with machine learning engineering or machine learning science, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.
• Experience (work or coursework) in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming

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