Senior MLOps Engineer - LLMs
Netherlands - Amsterdam
EUR 56K-76K (estimate) Senior-level Full Time
Tasks
- Apply inference optimizations including quantization continuous batching paged attention KV cache management
- Build ML pipelines for ingestion processing deployment evaluation
- Create templates and documentation for best practices
- Define and monitor SLIs SLOs for production model serving
- Deploy and optimize LLM serving infrastructure using vLLM
- Design and build production async API services with strict latency SLAs
- Establish MLOps best practices and guide teams adoption
- Implement A B testing infrastructure and canary deployments
- Implement monitoring for model performance latency throughput costs with budget alerting
- Manage Kubernetes and Slurm GPU clusters with multi tenant resource allocation
- Optimize GPU utilization and implement cost controls
- Optimize serving costs using model compression batching strategies infrastructure tuning
- Own CI CD for ML systems including automated testing model versioning deployment workflows
- Set up experiment tracking and model registry
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | Argo | Async API | Authentication | Authorization | B testing | CI/CD | Canary deployments | Continuous batching | Docker | FastAPI | Infrastructure as Code | KV cache | Knowledge Distillation | Kubeflow | Kubernetes | LLM | MLOps | MLflow | Machine Learning | Model Compression | Monitoring | Observability | PagedAttention | Pruning | Python | Quantization | Rate Limiting | Ray | SLI | SLO | Slurm | VLLM | Weights and Biases | “as-code”
Education
N/A
Roles
Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
Regions
Countries
States
Cities
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