26 days holidays + national bank holidaysIndividual training pathsOpportunity to develop and move within the companyNational and international mobility optionsYearly team activitiesFood canteen at the officeMotorK is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any kind.
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MotorK is the leading sales and marketing technology company in Europe, specialized in the automotive sector.
At MotorK our mission is to empower manufacturers and dealerships to sell more with innovative, cloud-based products and services to offer the best digital customer experience.
We are on a fast and ambitious trajectory and serving 90% of the automotive manufacturers.
To continue our growth, we are hiring new talents.
If you want to spark the future of the automotive world, join us.
About the Role As a Machine Learning Engineer at MotorK, you will be pivotal in driving innovation and improving customer experience.
You will develop and deploy machine learning models to power automotive maintenance prediction, product classification, and marketing asset generation.
Your work will directly impact the company's revenue, customer satisfaction, and overall business success.
What You'll Do Design, develop, and train machine learning models, including recommendation systems, predictive analytics, and classification algorithms.Collaborate with data engineers to extract, clean, and transform large datasets from various sources.Deploy models into production environments, ensuring scalability and reliability.Conduct A/B testing and other experiments to evaluate the impact of machine learning models on key metrics.Work closely with product managers and software engineers to translate business requirements into technical solutions.Provide technical guidance and mentorship to junior ML engineers on best practices and business-oriented problem-solving.Requirements5+ years experience as a machine learning engineer or data scientist in a digital product environmentStrong foundation in machine learning, including deep learning and statistical modelling.Proficiency in Python and relevant ML libraries (TensorFlow, PyTorch, Scikit-learn, or XGBoost).Experience with cloud platforms and MLOps, preferably AWS.Ability to explain complex technical concepts to non-technical stakeholders.Passion for data-driven innovation and a desire to make a significant impact.
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