Senior Machine Learning Engineer - Platform
Tasks
- Architect unified perception platform
- Build monitoring for model drift
- Define safety metrics and test sets
- Design real time machine learning systems
- Detect false positives and false negatives
- Detect latency regressions
- Develop evaluation frameworks for long tail safety events
- Improve system abstractions for scalability
- Integrate models across edge and cloud
- Manage model versioning and rollouts
- Mentor engineers on machine learning engineering correctness and performance
- Optimize messaging and backpressure
- Profile optimize end to end latency
- Translate research into production code
Perks/Benefits
- Comprehensive health plans
- Flexible working model
- Parental leave
- Professional development stipend
- Remote work
Skills/Tech-stack
AWS | Azure | CI/CD | Cloud Machine Learning | Computer Vision | Containerization | Data Drift | Data Drift Detection | Distributed Systems | Docker | Drift Detection | Edge Computing | GCP | Infrastructure as Code | Kubernetes | Machine Learning | Model Monitoring | Observability | Performance Profiling | Real Time | Real-time Systems | Risk Reasoning | Time Systems | “as-code”
Education
Bachelor of Science | Doctor of Philosophy | Master of Science | PhD
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