ML Platform Engineer
Tasks
- Architect model deployment monitoring and operations
- Build scalable infrastructure and internal tooling for ML workloads
- Collaborate with research and product teams on platform capabilities
- Contribute to architecture decisions and long term platform evolution
- Create abstractions for complex ML systems
- Design platform systems for model training and deployment
- Develop automation workflows and developer tools
- Drive observability automation reliability and platform usability improvements
- Improve workload scheduling monitoring debugging and resource management
- Own engineering challenges and deliver pragmatic scalable solutions
Perks/Benefits
- Flexible work environment across Europe
- Fully remote work
- High ownership role
- Professional growth opportunities
Skills/Tech-stack
Datadog | Debugging | Distributed Systems | GPU Computing | GitHub Actions | Infrastructure abstraction | Infrastructure automation | Kubernetes | Linux | Machine Learning | Model Deployment | Model Monitoring | Monitoring | Observability | Performance optimization | Python | Resource Management | Temporal | Terraform | Workflow Orchestration
Education
N/A
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