Senior Machine Learning

hace 7 días


Madrid, Madrid, España Kapsch Trafficcom Ag A tiempo completo

We are looking for a Senior Machine Learning Engineer to lead data-related iniciatives and be a technical referent for the team.
If you have a proficient background in information technology with a specific focus on ML and DL related to Data Science/Engineering, apply for the role and grow with usYour ResponsibilitiesYou design and build ML services to power our data products enabling data-driven decisions to improve traffic safety and prediction accuracyYou develop, train and test ML models to perform information retrieval and forecast analysis for mobility and traffic data domainUsing large data-sets to develop algorithms capable of learning and eventually making predictionsAnalyzing use cases of ML algorithms, ranking by success probability and applying the outcome to support business decisionsEnriching existing ML frameworks and librariesYou productize training models and package them into independent software servicesYou continuously improve deployed models by applying state-of-the-art techniques as well as code and data set quality, you are automating what is notContribution to software development in close collaboration with the teamYour profileBachelor Degree / Master Degree / PhD in Computer Science, Maths, Physics or relatedAt least 7 years of experience in data related field with special focus on productizing AI solutions.Solid knowledge of Machine Learning and Deep Learning field, experience in building up machine learning train and release pipelinesExperience with probabilistic models and classification modelsHands-on experience with tools like Tensorflow, Keras, XGboost, Scikit-learn, Pytorch, autoMLSolid experience with PythonKnowledge of SCRUM/ SAFe methologyExperience with cloudAnalytical mindset and solution driven personalityYou practice and live the agile mindsetGood oral and written EnglishOur offer :A market compliant gross salary in line with your qualifications and your job experiencePermanent roleFlexible working hoursHybrid working model (3 days of remote work/week)30 business days of annual leaveFlexible remuneration plan: transport card, restaurant card, private medical care, etc.Challenging the limits of mobility for a healthy world without congestionA hands-on onboarding with an experienced team in an international working environmentOngoing professional education and training measures



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