ML Platform Engineer
Tasks
- Architect model deployment monitoring and production serving
- Collaborate with research and product teams on platform capabilities
- Contribute to architecture and technical strategy
- Create ML system abstractions and developer tooling
- Design machine learning training and deployment platforms
- Develop internal tools for machine learning workloads
- Enhance observability automation reliability and developer experience
- Implement automation workflows for ML operations
- Improve workload scheduling monitoring debugging and resource management
Perks/Benefits
- Collaborative cross-functional environment
- Flexible across Europe
- Fully remote
- High ownership
- Professional growth opportunities
Skills/Tech-stack
Cloud infrastructure | Datadog | Debugging | Distributed Systems | GPU | GitHub | GitHub Actions | Infrastructure automation | Kubernetes | Linux | Machine Learning | Model Serving | Monitoring | Observability | Python | Temporal | Terraform | Workflow Orchestration
Education
N/A
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