You will work as part of our global Data Science team to provide data-driven AI solutions for our internal customers using state-of-the-art Machine Learning methods and tools. In collaboration with other Bosch units, you will enhance and operate our existing cloud-based solutions as well as explore new potential Machine Learning use cases. You will discover the full scope of our business data platform to generate insights and impact decision-making at Bosch.
Take responsibility: Collaborate with internal customers and an international agile team of developers and Data Scientists to extract insights from our global business data platform.
Help shape the future: Contribute to the future steering of Bosch as a member of the global cross-functional Business Intelligence team (xBI), working alongside Data Modelers, Data Engineers, and Business Analysts.
Use freedom and creativity: Embrace our agile values by sharing your ideas and experiences for the benefit of the team and the company.
Think entrepreneurially: Experience the start-up spirit within Bosch as part of the leading in-house provider for data and analytics solutions, contributing through entrepreneurial thinking and action.
Your profile
Education: M.Sc. or Ph.D. in Computer Science, Data Science, Mathematics, Statistics, Physics, Bioinformatics, or related fields.
Experience: Minimum of 3 years in AI Engineering.
AI Engineering Know-How: Proficiency in Python with high-quality code, experience deploying ML & DL models into production, expertise in MLOps, deployment technologies (Docker, Kubernetes, MLFlow, Azure DevOps, GitHub Actions, Jenkins), creating automated data and ML pipelines in Microsoft Azure, and developing Web APIs with Python. Experience retrieving and persisting data from various sources including relational/non-relational databases, cloud storages, vector databases, Hadoop, etc.
Machine Learning Know-How: Understanding of ML workflows such as training, fine-tuning, inference, and monitoring. Basic knowledge of machine and deep learning techniques like regression, classification, anomaly detection, time series forecasting, clustering, pattern recognition, data mining, and recommendation systems.
Personality: Team player, committed, responsible, and flexible.
Way of working: Agile, analytical, proactive, result- and solution-oriented, with high-quality coding standards.
Enthusiasm: Passionate about AI Engineering, Data Science, and advanced analytics; capable of developing interdisciplinary solutions and communicating complex issues simply.
Languages: Fluent in English, both written and spoken, with strong communication skills.
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