Senior MLOps & Cloud Solutions Engineer

This advert was translated automatically from Portuguese. Read the original.

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference. With over 300 specialized associates and around 15 nationalities, Bosch activities in Lisbon are focusing on sales, marketing, communication, training, nearshoring services and shared support for human resources services to Europe. The diversity, commitment and know-how of the team are the key success factors of this organization. Bosch Service Solutions develops and delivers Customer Experience, Mobility and Monitoring solutions for companies and their customers. Our teams find fast and efficient solutions for thousands of people on a daily basis – from claim management to life-saving emergency calls, among other services. Define the standards and become a pioneer together with around 9000 associates worldwide. - Machine Learning Model Integration. Machine Learning Model Integration. - Replace existing machine learning libraries with TensorFlow Lite. Replace existing machine learning libraries with TensorFlow Lite. - Integrate TensorFlow Lite with the build system and application. Integrate TensorFlow Lite with the build system and application. - Ensure compliance with open-source license rules. Ensure compliance with open-source license rules. - Develop and finalize integration tests for model integration. Develop and finalize integration tests for model integration. - Define and implement a format for model storage and versioning. Define and implement a format for model storage and versioning. - Create debugging or playback mechanisms to diagnose field issues. Create debugging or playback mechanisms to diagnose field issues. - Cloud Integration. Cloud Integration. - Implement model conformance verification logic for cloud-based deployments. Implement model conformance verification logic for cloud-based deployments. - Integrate TensorFlow for various detection algorithms (e.g., smoke detection). Integrate TensorFlow for various detection algorithms (e.g., smoke detection). - Standardize TensorFlow models for embedded systems. Standardize TensorFlow models for embedded systems. - Develop high-level model standardization for different detection algorithms. Develop high-level model standardization for different detection algorithms. - Establish methodologies to ensure correct model serialization Establish methodologies to ensure correct model serialization - Manage datasets related to machine learning model development and deployment. Manage datasets related to machine learning model development and deployment. - Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field. Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field. - Experience with other ML frameworks and libraries. Experience with other ML frameworks and libraries. - Familiarity with automotive or industrial applications of ML. Familiarity with automotive or industrial applications of ML. - Extensive experience with TensorFlow and TensorFlow Lite. Extensive experience with TensorFlow and TensorFlow Lite. - Proven track record of integrating ML models into production systems. Proven track record of integrating ML models into production systems. - Experience with model storage, versioning, and serialization. Experience with model storage, versioning, and serialization. - Strong proficiency in C++ and Python. Strong proficiency in C++ and Python. - Experience with build systems and continuous integration/continuous deployment (CI/CD) pipelines. Experience with build systems and continuous integration/continuous deployment (CI/CD) pipelines. - Familiarity with open-source software and ensuring compliance with licensing rules Familiarity with open-source software and ensuring compliance with licensing rules - Knowledge of standardization practices for embedded ML models. Knowledge of standardization practices for embedded ML models. - Experience with embedded systems and real-time processing.: Experience with embedded systems and real-time processing.: - Experience in developing integration tests for ML models. Experience in developing integration tests for ML models. - Ability to devise debugging and playback mechanisms for diagnosing field issues. Ability to devise debugging and playback mechanisms for diagnosing field issues. - Experience with cloud-based ML model deployment and conformance verification. Experience with cloud-based ML model deployment and conformance verification. - Strong communication skills and the ability to work in a collaborative team environment Strong communication skills and the ability to work in a collaborative team environment - Challenges in an international environment | Challenges in an international environment | - career opportunities in one of - the best companies in the - world | flexible hours | medical - services | discounts for employees | - sports and health related activities | canteen | good access to public transports | space for creativity