Machine Learning Engineer (Python TensorFlow SaaS) Cambridge to £90k Do you have experience of solving real-world problems via Machine Learning techniques? You could be progressing your career at a highly successful SaaS tech company that provides AI and ML products for automotive innovators to design better cars faster and achieve greater sustainability through Machine Learning. What's in it for you: Competitive salary - to £90k Private Health Care Life Assurance Up to 6% employer pension contribution 25 days holiday Complex and interesting work with continual learning opportunities Your role: As a Machine Learning Engineer you'll build the ML capabilities that power the product, typically you'll collaborate with the research team to productionise ideas that are ahead of the published literature, evaluating and integrating established methods or developing your own algorithms, ensuring reliability and maintainability within a complex, integrated codebase. You'll liaise with clients to understand engineering problems that the product can address and guide them through new ways of working as well as diagnosing complex issues to analyse if it's a data quality issue, unexpected model behaviour, a configuration problem or a genuine bug. You'll be at the intersection of shaping product direction, balancing what ML researchers envision with what customers actually need and what is realistic to build and maintain in production. Location / WFH: You'll join the team in Cambridge, ideally once a week (potentially once a month) with flexibility to work from home most of the time. About you: You have strong theoretical and practical understanding of the foundations of Machine Learning with experience of applying these to solve real-world problems You have strong Python skills, including TensorFlow and PyTorch ML frameworks You enjoy solving complex problems proactively but know when to ask for help from domain experts, researchers and engineers You have strong foundations in probabilistic modelling (Gaussian processes, Bayesian methods, uncertainty quantification) You're a confident communicator, comfortable liaising with clients Apply now

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