Master Thesis focusing on developing machine learning models for lithium - ion cell sorting at Fraunhofer LBF. Involvement in innovative projects addressing circular economy in battery recycling.
About the role
- Machine Learning Software Engineer bridging machine learning research and production deployment at Mobileye. Developing robust solutions and managing scalable production systems.
Responsibilities
- Your role will include developing production deployment systems for classical and machine learning algorithms from research and building robust, scalable inference pipelines.
- You will develop primarily in Python and infrastructure tools (Kubernetes, Docker, etc.), taking part in both maintaining existing deployment systems and developing new production capabilities.
- Finally, you will need to learn and implement new deployment technologies and best practices that can address emerging production challenges as they arise, while staying current with the latest MLOps and inference optimization techniques.
Requirements
- B.Sc. in Computer Science, Software Engineering, or related technical field.
- 2+ years of experience in production software development, preferably in ML deployment.
- Strong problem-solving skills and ability to tackle complex, real-world production challenges.
- Proficiency in Python and experience with containerization and orchestration technologies (Docker, Kubernetes)- advantage.
- Hands-on experience with model serving frameworks and inference optimization- advantage.
- Background in distributed systems and cloud infrastructure- advantage.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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