Manager en sciences computationnelles IA/ML
Remote • Paris
Posted 14h ago
Job Location
Paris
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
As an AI/ML computational scientist, you will design, develop, and operationalize artificial intelligence and machine learning solutions for enterprise clients. This involves combining custom models with third-party and cloud AI services to deliver production-ready results. Your role will span the entire solution lifecycle, from assessing client needs and data, to selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models). You will also design scalable data pipelines and MLOps/LLMOps for training and production, ensuring the quality, value, and reliability of deployed systems.
Responsibilities
- 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 using DevOps & MLOps practices.
- Customize and apply Deep Learning and Generative AI models for various use cases based on business needs, data availability, and system/infrastructure requirements, including edge devices and HPC.
- Participate in research and development of new AI and high-performance computing algorithms, models, and simulations for complex business problems.
- Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input data for training and production.
- Implement and maintain effective data storage and retrieval mechanisms for models and knowledge using appropriate tools.
- Justify the value of modeling approaches in business problem-solving.
- Collaborate with business and technical teams, including users, use case representatives, business leaders, engineers, architects, and UI designers, to achieve end-to-end project goals and ensure production integration.
Requirements
- Professional experience as a machine learning engineer or scientist with experience deploying models into large-scale production, including monitoring, alerting, automated bug reporting, and auditing.
- Strong experience applying theoretical computer science foundations, including computer system architecture, systems engineering, and programming.
- Demonstrable experience with distributed computing systems and architectures, potentially including big data, high-performance computing, engineering simulations, scientific computing, grid computing, cloud computing, and distributed networks.
- Experience building and deploying AI/ML-based software in a cloud environment.
- Bachelor's degree or equivalent.