Machine Learning Infrastructure Engineer, Model Inference
Tasks
- Build model API orchestration system
- Define and implement infrastructure scaling strategies
- Design Kubernetes clusters for model inference and training
- Develop optimize and maintain model serving infrastructure
- Enhance GPU utilization for ML workloads
- Optimize throughput for model workloads
- Scale backend infrastructure for AI model deployment
Perks/Benefits
- 401k matching
- Commuter benefits
- Comprehensive medical, dental, vision
- Flexible PTO
- Flexible spending accounts
- Generous time off
- HSA contribution
- Lifestyle Wallet
- Mental health support
- Paid parental leave
- Personal device allowance
- Sabbatical leave
Skills/Tech-stack
API Development | Ansible | CUDA | Container Registry | Custom Resource Definitions | Distributed Systems | Docker | GPU Utilization | Git | GitOps | Inference Server | Infrastructure as Code | Kubernetes | Kubernetes Custom Resource Definitions | Kubernetes Operators | Machine Learning | Machine Learning Model | Machine Learning Model Serving | Model Serving | NVIDIA Triton | NVIDIA Triton Inference | NVIDIA Triton Inference Server | PyTorch | TensorFlow | TensorRT-LLM | Terraform | Triton Inference Server | VLLM | “as-code”
Education
N/A
Regions
Countries
States
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