Senior ML Engineer, Fractal

• Strong demonstrated experience using ML Training frameworks (mainly TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)
• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance
• Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)
• Experience with high-volume data processing and real-time streaming architectures
• Strong understanding of recommendation system design and personalisation algorithms
• Familiarity with Generative AI and its applications in production settings
• Good communication and analytical problem-solving skills
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Desirable

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance
• Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems

• End Date: September 30, 2026