Engineering Manager, Model Inference
Tasks
- Architect and scale inference infrastructure
- Benchmark and eliminate inference bottlenecks
- Collaborate with ML research on model optimization quantization deployment
- Define inference system technical direction
- Develop AI inference APIs
- Ensure reliability efficiency observability
- Establish engineering standards and operational processes
- Lead and grow AI inference engineering team
- Lead incident response
- Optimize batching throughput latency GPU utilization
- Plan and execute cross-functional projects
- Recruit, mentor, and develop engineering talent
Perks/Benefits
- 401k matching
- Commuter benefits
- Flexible PTO
- Flexible spending accounts
- Generous time off
- HSA contribution
- Lifestyle Wallet
- Mental health support
- Paid parental leave
- Personal device allowance
- Sabbatical leave
- Therapy and coaching
Skills/Tech-stack
APIs | Attention Mechanism | Batching | Distributed Systems | Docker | Expert parallelism | FlashAttention | GPU Performance | GPU performance analysis | Grouped Query Attention | Incident Response | Kernel Fusion | Kubernetes | Multi-head attention | Observability | Performance Analysis | Pipeline parallelism | PyTorch | Quantization | Real Time | Real-time Systems | Tensor Parallelism | TensorFlow | TensorRT | Time Systems | Transformer | VLLM
Education
Regions
Countries
States
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