LLM Research Scientist (Pre-training & Computer Vision & Adversarial Robustness)
Math & ScienceRemoteHourly contractAlways-open talent poolPosted Aug 5
Mercor keeps this listing open to build a pool of candidates. Applying puts you in the pool; it is not a single fresh opening.
We're looking for experienced machine learning researchers with hands-on experience training and improving deep learning models end-to-end, across vision and language. You'll work on well-scoped empirical open-ended ML research problems.
Responsibilities
- Train image classifiers and generative image models from scratch, and fine-tune open-weight language models.
- Get the most out of limited data, compute, and model-size budgets.
- Make models robust — to adversarial inputs and to adversarial conversations.
- Compress models to meet hard size and latency constraints without sacrificing accuracy.
- Diagnose and resolve training issues.
Experience with
- Adversarial training of image classifiers (e.g. PGD-based training, TRADES).
- Evaluating robust accuracy under standard threat models (e.g. L∞ attacks, AutoAttack) and avoiding gradient-masking pitfalls.
- Managing the robustness–accuracy trade-off and robust overfitting.
Experience with
- Training image classifiers end-to-end, especially for fine-grained recognition (many visually similar classes, few examples per class).
