Machine Learning Engineer (m/w/d) Cloud

Microvast Holdings, Inc.; Ludwigsfelde; Vor Ort; EUR 60.000 - 90.000; Vollzeit

Zusammenfassung

A leading company in the technology sector is seeking a Cloud & Machine Learning Engineer to enhance their innovative data-driven solutions. You will be responsible for designing a robust cloud infrastructure and deploying machine learning models for advanced analytics and system safety. Ideal candidates have a strong foundation in computer science or engineering, with practical experience in cloud services and machine learning frameworks. This role offers an exciting opportunity to work on cutting-edge projects in a collaborative environment.

Qualifikationen

• Experience in building and managing cloud infrastructures with providers.
• Strong knowledge of Machine Learning algorithms for data analysis.
• Programming skills in Python or MATLAB/Simulink.

Aufgaben

• Design, build, and maintain scalable cloud infrastructure.
• Implement methods for State of Health (SOH) estimation.
• Develop predictive maintenance models and algorithms for data optimization.

Kenntnisse

Machine Learning

Cloud Infrastructure Management

Data Analysis

Communication

Ausbildung

Degree in Computer Science, Engineering, Mathematics, or related field

Tools

AWS

Google Cloud

Microsoft Azure

TensorFlow

PyTorch

Git

Jenkins

Jobbeschreibung

We are looking for a talented and driven Cloud & Machine Learning Engineer to join our team and play a key role in building intelligent, data-driven solutions. In this position, you will be responsible for designing, developing, and maintaining a scalable and secure cloud infrastructure that supports advanced analytics and system monitoring.

Additionally, you will design and deploy solutions for thermal runaway detection to enhance system safety and reliability, and create predictive maintenance models to anticipate failures and maximize uptime. You will collaborate closely with cross-functional teams to deliver data-driven solutions tailored to diverse business needs.

We are looking for a talented and driven Cloud & Machine Learning Engineer to join our team and play a key role in building intelligent, data-driven solutions. In this position, you will be responsible for designing, developing, and maintaining a scalable and secure cloud infrastructure that supports advanced analytics and system monitoring.

Additionally, you will design and deploy solutions for thermal runaway detection to enhance system safety and reliability, and create predictive maintenance models to anticipate failures and maximize uptime. You will collaborate closely with cross-functional teams to deliver data-driven solutions tailored to diverse business needs.

Your profile:

• A degree in Computer Science, Engineering, Mathematics, or a related field
• Experience in building and managing cloud infrastructures, preferably with known providers like AWS, Google Cloud, or Microsoft Azure
• Strong knowledge of Machine Learning and the application of algorithms for data analysis and modeling
• Experience with programming languages such as Python or MATLAB/Simulink, and with Machine Learning frameworks (e.g., TensorFlow, PyTorch)
• Preferred is experience in implementing BMS methods like SOH estimation, thermal runaway detection, or predictive maintenance
• Familiarity with automation tools and CI/CD processes (e.g. Git, Jenkins)
• Team player with communication skills (English preferred, German & Chinse are advantageous) in an agile work environment

Your tasks:

• Design, build, and maintain a scalable and secure cloud infrastructure
• Integrate data collection processes into cloud architecture
• Process and analyze large datasets collected in the cloud using Machine Learning techniques
• Develop and implement algorithms for data modeling and optimization of analysis processes
• Implement methods for State of Health (SOH) estimation, enabling accurate assessments of system and component health over time
• Develop and deploy solutions for thermal runaway detection to improve system safety and reliability
• Create predictive maintenance models to anticipate potential failures and optimize system uptime
• Collaborate with cross-functional teams to develop data-driven solutions for various business requirements