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Remote role, mid-level senior ML position, metro location and strong brand drive high competition.
Core ML engineering skills transfer across industries, but scientific/R&D emphasis increases sector specificity.
Requires MSc/PhD, 5+ years, deep ML expertise and production MLOps experience, making filters highly strict.
Design, build, and maintain scalable, production-grade machine learning systems and pipelines with modern engineering practices (CI/CD, testing, monitoring).
Develop novel machine learning algorithms and models that are experimentally validated and deployed as reliable, scalable products delivering measurable value.
Collaborate cross-functionally with data scientists, software engineers, and domain experts to translate complex scientific and business problems into deployable ML solutions.
MSc or PhD in a quantitative field such as Computer Science, Mathematics, Physics, or Engineering.
Typically 5+ years of hands-on experience designing, prototype, productionising, maintaining, and scaling ML/data science products in complex environments.
Strong expertise in machine learning algorithms, statistical modelling, software development (Python, Go, Java, C++), and advanced SQL.
Experience with modern ML engineering practices including MLOps, model lifecycle management, CI/CD, monitoring; hybrid work model; up to 10% travel expected.
Experienced ML engineer comfortable with transitioning research algorithms into scalable production-grade products with a scientific and engineering rigor.
Ability to work in cross-disciplinary teams and influence stakeholders across various technical and business domains.
Familiarity with advanced ML techniques relevant to operational, scientific, R&D domains including NLP, optimisation, generative AI, and scientific workflows.