Senior ML Engineer (Evaluation)
Tasks
- Deploy services and manage rollbacks
- Ensure eval stack testing and validation
- Implement production observability and alerting
- Maintain inference services
- Manage distributed compute resources
- Orchestrate evaluation pipelines
- Organize eval databases and artifacts
- Own MLOps end to end
- Run evaluations at scale
- Set engineering direction and architecture
- Verify model integrations and expected behavior
Perks/Benefits
- Autonomy
- Commuting subsidy
- Learning and development budget
- Offsites and team events
- Pension plan
- Vacation days
Skills/Tech-stack
Alerting | Artifact versioning | CI Code Review | CI/CD | CUDA | Code review | Dagster | Distributed Systems | Docker | Evaluation | GPU Computing | Incident Response | Inference | Inference Server | Integration Testing | Kubernetes | MLflow | Model Registry | Model Serving | Observability | Python | Ray | Tensor Shapes | TensorRT-LLM | Testing | Tokenization | Triton Inference | Triton Inference Server | Unit Testing | VLLM
Education
N/A
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