Staff Machine Learning Engineer
Tasks
- Apply automated testing for ML systems
- Architect real time ML serving
- Build low latency signal path for production feedback
- Define data contracts for model inputs and outputs
- Deploy automated retraining and redeployment pipelines
- Develop cloud production systems with real time endpoints
- Implement MLOps for model monitoring and governance
- Implement secure software development practices
- Integrate partner systems with ML pipelines
- Optimize model deployments for latency and throughput
- Own end-to-end machine learning lifecycle
- Set engineering standards and lead technical mentorship
Perks/Benefits
- 401k match
- Dental insurance
- Disability insurance
- EAP support
- Life insurance
- Medical insurance
- Paid time off
- Vision insurance
- Wellbeing resources
Skills/Tech-stack
AWS | Alerting | Auto Scaling | Automated retraining | CI/CD | Cloud Computing | Concept drift | Concept drift detection | Containers | Data Drift | Data Drift Detection | Deep learning | Distributed Systems | Drift Detection | Generative AI | GitHub Actions | Gradient boosting | Infrastructure as Code | Kubernetes | Language Models | Large Language Models | Low Latency | Low-Latency Systems | MLOps | Machine Learning | Model Monitoring | Monitoring | PyTorch | Python | Secure Software | Secure Software Development | Self-Supervised Learning | Self-supervised | Software development | Supervised Learning | TensorFlow | Terraform | Test-Driven | Test-Driven Development | Transformers | “as-code”
Education
Regions
Countries
States
Cities
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