ML & Data Engineer for Edge & Hybrid Cloud for Digital Twin (f/m/div.)

ML & Data Engineer for Edge & Hybrid Cloud for Digital Twin (f / m / div.)

Groenerstraße 9, 71636 Ludwigsburg, Germany

Full-time

grow platform GmbH

Company Description

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. Welcome to Bosch.

The grow platform GmbH is looking forward to your application!

Job Description

We make machines speak! Find out how by becoming one of our team members in Bosch’s Home of Intrapreneurs. Bosch Digital Twin Industries is a corporate start-up that is going global and faces huge business potential which now needs to be realized.

Therefore, we need you as contributors, shapers & fellow team members in a multi-cultural, innovative and ambitious environment.

Together we will take human and machine intelligence to a next level of human-machine collaboration based on learning algorithms & real-world challenges with large industrial machinery.

As an ML & Data Engineer for Bosch Digital Twin Industries (BDTI), you will be responsible for developing and implementing our digital twin solution for edge & hybrid cloud setups.

This involves implementing ML & data engineering pipelines using state-of-the-art frameworks / databases and deploying them in a container-based manner using Docker / Kubernetes.

• Container-Based Solutions : Design and explore IoT and cloud solutions using Docker / Kubernetes for edge-based machine learning use cases.
• Data Flow Streamlining : Streamline data flow pipelines including data ingestion, storaging, deploying ML models, interfacing with cloud, connecting to backend / frontend;

including the selection of ideal software technologies, databases and relevant frameworks (e.g. databases, orchestration, MLOps tools).

• Cloud-Agnostic Software Solutions : Develop cloud-agnostic software solutions that can be deployed on any hardware or cloud environment with minimal modifications.
• MLOps Concept Development : Develop and implement a MLOps concept tailored for digital twin solutions.

Qualifications

• Education : Master's degree in computer science, data science, or a related field.
• Experience and Know-How : Minimum of 3 years of experience in machine learning algorithms and frameworks, with a focus on scalable infrastructure and automation for deploying and managing ML models in production environments.
• Technical Proficiency : Python, skills in relevant ML & data engineering tools / frameworks (e.g. MLflow, Kubeflow, Airflow, MongoDB, time-series databases).

Experience with containerization technologies (Docker, Kubernetes, OpenShift) and cloud platforms (AWS / Azure) is preferred.

• Communication & Collaboration : Excellent communication and collaboration skills, with an ability to work effectively in cross-functional teams.
• Problem-solving : Strong analytical skills with a focus on delivering business value through efficient and reliable ML operations.
• Languages : You are business fluent in English, other languages are welcome.

Additional Information

The contractual work location is Ludwigsburg.

You want to work remotely or part-time - we offer great opportunities for mobile working as well as different part-time models.

Feel free to contact us.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Here you get more information about Digital Twin : Digital Twin Bosch Global Software Technologies PVT LTD (bosch-softwaretechnologies.com)

Digital Twin is a trend-setting business model innovation financed by the grow platform GmbH, the Bosch incubator platform.

Get more information here : What's in it for you? grow platform

Need further information about the job?

Prahallad C R (Functional Department)

49 711 811 12926

Patrick Schlachter (Functional Department)

49 15255472610

Need support during your application?

Nelly Ehrmann (Human Resources)