Lead Machine Learning Engineer, Inference & Performance
Tasks
- Configure autoscaling for serving
- Deploy LLM models in production
- Handle mixed workloads gracefully
- Identify training bottlenecks
- Implement batching and quantization
- Improve throughput per dollar
- Manage KV cache strategies
- Measure GPU utilization
- Minimize latency
- Operate models on GPU clusters
- Optimize LLM inference
- Optimize attention implementations
- Profile training runs
- Translate client requirements into AI architectures
- Tune LLM serving throughput
Perks/Benefits
- 401k employer match
- Bereavement leave
- Comprehensive health insurance
- Employee referral bonuses
- Paid Holidays
- Paid leave
- Parental leave
- Sick leave
Skills/Tech-stack
Attention Mechanism | Batching | CUDA | Data Engineering | FlashAttention | GKE | GPU Architecture | Google Cloud | KV cache | Kubernetes | Profiling | Python | Quantization | SGLang | SQL | Shell Scripting | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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