Principal MLE @ A16Z Backed Security Startup | $200 - $250k + Equity
Tasks
- Adapt models to new domains
- Automate model release
- Build dashboards
- Build training pipelines
- Configure batching and autoscaling
- Convert reviewer feedback to training data
- Create evaluation infrastructure
- Enable canary and rollback
- Ensure reproducible model fine tuning
- Implement experiment tracking
- Implement model update versioning
- Monitor model drift
- Optimize low-latency inference
- Run automated evaluation
- Serve models in production
- Set ML infrastructure standards
- Set regression gates
- Version datasets
Perks/Benefits
Skills/Tech-stack
Autoscaling | Batching | CI/CD | Calibration | Canary Deployment | Cloud infrastructure | Constrained decoding | Containers | Cost Optimization | Dataset versioning | Distributed Training | Drift monitoring | Evaluation Harness | Experiment tracking | Fine Tuning | Inference engine | Latency optimization | LoRA | Model Serving | Observability | Precisión | PyTorch | Python | Recall | Regression testing | Rollback | Structured Output | Supervised Fine Tuning | TensorRT-LLM | VLLM
Education
N/A
Regions
Countries
States
Cities
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