Inference Infrastructure Engineer for Large-Scale AI
causal
Causal is building a Large Physics foundation Model and seeks infrastructure engineers for high-throughput, low-latency inference at scale in San Francisco. You will work on evaluating physical observations, backtesting, and large-batch workflows, collaborating with researchers to push model performance. We value deep learning expertise, GPU-aware optimization, and production-grade engineering. Proficiency with PyTorch or JAX, Kubernetes-based orchestration, and open‑source inference tooling is #J-18808-Ljbffr causal
Vacancy posted 2 days ago
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