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 Engineer managing high performance computing environment and model serving initiatives at Latent Labs. Collaborating on innovative biological solutions with interdisciplinary teams.
Responsibilities
- Deploy, maintain, and optimize production and research compute clusters
- Design and implement scalable and efficient ML inference solutions
- Develop dynamic / heterogeneous compute solutions for balancing research and production needs
- Contribute to productizing model APIs for external use
- Develop infrastructure observability and monitoring solutions
Requirements
- Deep experience with Kubernetes and containerized workflows
- Experience with major cloud platforms (AWS, GCP, Azure)
- Knowledge of DevOps and related tools (Terraform, etc)
- Knowledge of HPC frameworks (Slurm, Ray, etc)
- Production engineering & reliability experience
- PyTorch & distributed computing experience
Benefits
- Private health insurance
- Pension/401(K) contributions
- Generous leave policies (including gender neutral parental leave)
- Hybrid working
- Travel opportunities and more
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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