Tasks:
- * Benchmark inference engine performance
- * Build CI CD infrastructure for endpoint deployment
- * Build CI/CD infrastructure for image releases
- * Build CI/CD infrastructure for inference engines
- * Deploy AI model serving systems
- * Deploy frontier models to production
- * Design and optimize infrastructure for large-scale machine learning workloads
- * Develop high-performance inference systems
- * Improve infrastructure reliability and efficiency
- * Manage continuous deployment and feature rollouts
- * Manage inference service autoscaling
- * Monitor inference engine performance across production workloads
Perks/Benefits:
Skills/Tech stack required:
[AI model] [AI Model Serving] [Autoscaling] [C#] [C++] [CI/CD] [Cloud Computing] [Continuous Deployment] [Distributed Systems] [Edge Computing] [High Availability] [High-availability systems] [Inference Systems] [Learning systems] [Low Latency] [Low-Latency Systems] [Machine Learning] [Machine learning systems] [Model Serving] [Performance Benchmarking] [Production Monitoring] [Python]
Educational requirements:
[Bachelor's Degree in Computer Science or related technical field] [Master's Degree in Computer Science or related technical field]
Role(s):
[AI Engineer] [Engineer] [Inference Engineer] [Infrastructure Engineer] [Machine Learning Infrastructure Engineer]