Senior Applied Scientist, Efficient LLM Inference & Model Optimization
Palo Alto, California, United States
USD 195K-262K Senior-level Full Time
Tasks
- Collaborate with machine learning engineers
- Define efficient LLM and VLM inference programs
- Design evaluation for quality and numerical stability
- Develop prototypes for inference
- Evaluate latency throughput and cost per token
- Execute ablation studies
- Invent quantization methods
- Mentor engineers on experimental design
- Own research projects
- Productionize model compression methods
- Publish technical reports and open source artifacts
Perks/Benefits
- 401k plan
- Career growth and learning opportunities
- Collaborative culture
- Disability insurance
- Flexible work arrangements
- Health insurance
- Life insurance
- Parental leave
- Remote Work Reimbursement
Skills/Tech-stack
CUDA | Cache Compression | Co Optimization | Decoding algorithms | Evaluation methodology | KV Cache Compression | KV cache | Knowledge Distillation | Kv cache reuse | Language Models | Large Language Models | Latency optimization | Long Context | Long context inference | Machine Learning | Mixture of Experts | Model Compression | Model Runtime | Model Runtime Co Optimization | Numerical Stability | PyTorch | Python | Quantization | Quantization aware training | Speculative decoding | Statistical Reasoning | Tail Latency | Transformer Inference | Triton | Vision Language Models | Vision-language
Education
Regions
Countries
States
Cities
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