Deep AI Native Software Engineering
Pubblicato il 25-09-2026 - Accenture Italia in Milano
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. xysqume
- 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
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