ML Scientist: Adversarial Robustness & Efficient Vision
Listed on 2026-10-11
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Research/Development
Obsidian is seeking experienced machine learning researchers to tackle open-ended empirical ML problems across vision and language. You will train and improve deep learning models end-to-end, from data preparation to deployment, focusing on robustness and efficiency.
Responsibilities include training image classifiers and generative models, mitigating data and compute constraints, and refining LLM post-training behaviors.
This posting is for the ML Scientist:
Adversarial Robustness & Efficient Vision role at Mercor, based in Chicago, IL, United States.
The position is based in Chicago, IL, United States.
This opportunity is part of our work in Bio & Pharmacology & Health, Other.
The advertised compensation is 130..
We aim to respond to suitable candidates as soon as possible.
Full responsibilities and requirements are described in the listing above.
Learn more about the ML Scientist:
Adversarial Robustness & Efficient Vision role in the description above.
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