24 hours ago
Ariana, TunisiaMid Level
Responsibilities
- Support AI project lifecycles from data exploration and preprocessing through model training, evaluation, and deployment.
- Develop and optimize machine learning models using Python and frameworks such as PyTorch or TensorFlow.
- Prepare, clean, batch, augment, normalize, and manage datasets for training and inference.
- Contribute to feature extraction, feature engineering, model validation, performance tuning, and reusable AI pipelines.
- Help deploy AI/ML components as APIs, microservices, cloud endpoints, or lightweight edge and embedded runtimes.
- Collaborate with data engineers, architects, business analysts, and multidisciplinary teams to translate requirements into AI solutions.
- Participate in proof-of-concepts, experimentation, and continuous improvement of AI components.
- Explain complex technical concepts to technical and non-technical audiences while managing multiple project phases.
Requirements
- Bachelor’s or Master’s degree in Artificial Intelligence, Data Science, Computer Science, Applied Mathematics, or a related field.
- Practical experience applying machine learning techniques to real-world problems and building and evaluating ML models.
- Strong understanding of machine learning principles, evaluation methodologies, optimization techniques, classical ML algorithms, and deep learning architectures.
- Experience with Python, PyTorch, TensorFlow, NumPy, Pandas, and related data manipulation or ML libraries.
- Ability to preprocess and clean structured, unstructured, sensor, or high-dimensional data.
- Understanding of dataset management for training and inference, including batching, augmentation, and normalization.
- Basic understanding of deploying ML models outside notebooks as APIs, microservices, or embedded runtimes.
- Familiarity with on-device inference, quantization, pruning, compression, lightweight runtimes, and portable execution formats.
- Exposure to computer vision, image processing, time-series data, sensor-derived signals, or biometric-style data is preferred.
- Strong analytical, problem-solving, communication, teamwork, adaptability, and learning abilities.
- Excellent communication skills in English and French and comfort working in Agile, multidisciplinary teams.
Benefits
- Multicultural and inclusive team environment with a supportive atmosphere promoting work-life balance.
- Hybrid work arrangement depending on the project.
- Career growth programs, training, and certifications in cutting-edge technologies.
- Opportunities to work on national and international projects.
- Referral program with bonuses for talent recommendations.
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.