Adversarial ML Scientist: Robustness & Efficient Models
Listed on 2026-10-07
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Research/Development
Obsidian is seeking experienced ML researchers to tackle end‑to‑end deep learning challenges across vision and language. You will train image classifiers, generative models, and open‑weight LLMs, while pushing robustness, efficiency, and deployment‑ready performance on high‑scale data.
Applicants should have 3+ years in ML research, expertise in PyTorch/JAX/Tensor Flow, and a strong publication or open‑source track record from a top university or FAANG‑level environment.
As a Adversarial ML Scientist:
Robustness & Efficient Models, you will play an important part at Obsidian in San Francisco, CA, United States.
This role, Adversarial ML Scientist:
Robustness & Efficient Models at Obsidian, could be your next career step.
Are you ready to take on the Adversarial ML Scientist:
Robustness & Efficient Models role at Obsidian?
We would love to welcome a new Adversarial ML Scientist:
Robustness & Efficient Models to our group in San Francisco, CA, United States.
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