ML Platform Engineer
Tasks
- Architect systems for model deployment monitoring and operation
- Build scalable infrastructure and internal tooling for machine learning workloads
- Collaborate with research and product teams to deliver platform capabilities
- Contribute to architecture decisions and long term platform evolution
- Create abstractions and developer tools for complex machine learning systems
- Design platform systems for machine learning training evaluation deployment and production serving
- Develop automation workflows and internal tools for researchers and engineers
- Drive improvements in observability automation reliability and developer experience
- Improve workload scheduling monitoring debugging and resource management
Perks/Benefits
- Collaborative environment
- Flexible work across Europe
- Fully remote work environment
- High ownership role
- Influence over platform architecture and technical direction
- Professional growth opportunities
Skills/Tech-stack
Data-intensive | Data-intensive workloads | Datadog | Debugging | Distributed Systems | GPU Computing | GitHub Actions | Infrastructure automation | Kubernetes | Linux | Machine Learning | Model Serving | Monitoring | Observability | Performance optimization | Python | Resource Management | Terraform | Workflow Orchestration
Education
N/A
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