– Substantial experience (2+ years) as a Machine Learning Engineer or a similar role, with a strong focus on MLOps practices.
– Proficiency in machine learning frameworks and tools, such as TensorFlow, PyTorch, or scikit-learn.
– Expertise in building and deploying production-ready machine learning pipelines, including data preprocessing, model training, and model serving.
– Strong understanding of software engineering best practices, including version control, CI/CD, and containerisation.
– Familiarity with cloud computing platforms (e.g. AWS, GCP, or Azure) and experience in deploying and managing machine learning models in the cloud.
– Excellent problem-solving skills, with the ability to work independently and as part of a cross-functional team.
– Passion for staying up-to-date with the latest advancements in machine learning and a willingness to learn and adapt to new technologies.
– Strong problem-solving and collaboration skills.
– Proficiency in English, both written and spoken.