YOU AREAs 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 WORKFormulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutionsDevelop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOpsCustomize 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 HPCEngage 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 sitesWork with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and productionImplement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate toolsJustify the value of model approaches in business problemsCollaborate 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 productionEDUCATIONBachelor's Degree in Computer Science, Computer Engineering, Data Science, or a related fieldBasic (required) QualificationWork 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 programmingPreferred QualificationProficiency 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, SQLStrong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholdersStrong client-facing skillsets in a consulting environmentStrong cross-functional skills with the ability to collaborate with a variety of internal and client-side teamsEntrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation#J-18808-Ljbffr

📌 Deep Ai Native Software Engineering (Milano)
🏢 Accenture Italia
📍 Milano