PropTexx is seeking a highly skilled Machine Learning Engineer to join our team in Valbonne. The successful candidate will play a crucial role in developing and implementing advanced machine learning algorithms specifically designed for image generation tasks. This is a hands-on, full-time position that requires a deep understanding of machine learning models, data handling, and cloud-based deployment solutions.

• Algorithm Development: Design, develop, and implement machine learning algorithms for image generation applications.
• Training Pipelines: Create and manage complex training pipelines, ensuring they are optimized for performance and scalability.
• Data Handling: Efficiently manage and preprocess large datasets necessary for training and validating models.
• Cloud Deployment: Handle the containerization and deployment of machine learning models using AWS, GCP, or Azure services.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders to integrate machine learning solutions into our products.
• Optimization: Continuously improve algorithms and models for better accuracy, efficiency, and scalability.

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Experience: Proven experience as a Machine Learning Engineer, particularly with image generation algorithms and training pipelines.
• Technical Skills:
• Proficiency in Python and relevant libraries (TensorFlow, PyTorch, etc.).
• Experience with cloud platforms such as AWS, GCP, or Azure, including containerization (Docker, Kubernetes).
• Strong understanding of machine learning frameworks and tools.
• Familiarity with data preprocessing techniques and tools.
• Knowledge of deployment and CI/CD processes in a cloud environment.
• Problem-Solving: Strong analytical and problem-solving skills.
• Team Player: Excellent communication and teamwork abilities.
• Adaptability: Ability to work in a fast-paced, dynamic environment and manage multiple projects simultaneously.