Significant experience designing and deploying machine learning systems in production environments.
Strong software engineering skills in Python , with experience building maintainable, tested, and production-quality code.
Strong experience with large-scale data processing using technologies such as PySpark and Databricks .
Experience designing and building ML pipelines across the full lifecycle, from data preparation and model development through to deployment and monitoring.
Experience developing deep learning models using frameworks such as PyTorch, TensorFlow, or similar .
Experience with multimodal machine learning, representation learning, or embedding models , combining data sources such as images, text, structured metadata, or behavioural signals.
Strong understanding of modern deep learning architectures, particularly Transformers, foundation models, multimodal learning, and representation learning techniques .
Experience working with distributed computing, large datasets, and scalable model training or inference systems.
Familiarity with cloud platforms and modern MLOps practices.
Strong communication skills and the ability to collaborate effectively with scientists and engineers.
A pragmatic mindset, balancing technical excellence with delivering business value.
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