Software Engineer, Machine Learning Infrastructure - Generative AI
San Francisco, CA; Sunnyvale, CA; Seattle, WA
USD 137K-299K Mid-level Full Time
Tasks
- Build generative AI inference and fine tuning infrastructure
- Build observability and reliability tooling
- Create data pipelines for model training and evaluation
- Design scalable model serving and batch inference systems
- Develop backend APIs and services
- Implement GPU autoscaling and utilization
- Integrate LLM gateway agent gateway and guardrails
- Optimize latency throughput and cost of GPU inference
- Support production operations with monitoring and incident response
Perks/Benefits
Skills/Tech-stack
APIs | AWQ | AWS | Autoscaling | Backend Development | Batch inference | DPO | Data Pipelines | Debugging | Distributed Systems | FP8 | Fine Tuning | GCP | GPTQ | GPU Utilization | GPU autoscaling | INT8 | Incident Response | KV cache | Kubernetes | Latency optimization | LoRA | Machine Learning | Machine Learning Infrastructure | Model Serving | Monitoring | Observability | Python | Quantization | RAG | SFT | SGLang | TensorRT-LLM | Throughput Optimization | Tracing | VLLM | Vector Databases
Education
Regions
Countries
States
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