LLM Research Scientist, Pre-training, Computer Vision & Adversarial Robustness (Remote, Contract, $100–$120/hr) — Mercor via AI Gig Scout

Mercor is looking for experienced machine learning researchers with hands-on experience training and improving deep learning models end to end, across vision and language, for flexible, project-based remote contract work on well-scoped, open-ended empirical ML research problems. The role is listed at $100–$120/hr.

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 adversarial conversations; compress models to meet hard size and latency constraints without sacrificing accuracy; and diagnose and resolve training issues.

They want strong expertise in one or more of: adversarial robustness (PGD-based training, TRADES, AutoAttack evaluation), efficient computer vision and model compression (quantization, pruning, distillation, on-device or edge budgets), generative image modeling (diffusion, GANs, VAEs, flows, FID), LLM post-training and behavioral robustness (SFT, DPO, RLHF, RLAIF), or multilingual pre-training and tokenizer design. General qualifications: 3+ years of ML research experience (PhD research counts), strong PyTorch, JAX, TensorFlow or similar, and a degree from a top-100 university, experience at a FAANG or comparable AI company, or an equivalent research track record.

Details and apply link: https://aigigscout.com/jobs/mercor/llm-research-scientist-pre-training-and-computer-vision-and-adversarial-robustness-list-aaabn9g5kyvgtlh1jqzgvpvy?utm_source=kubernetesjobs&utm_medium=jobboard&utm_campaign=aigigscout_growth

Disclosure: posted by AI Gig Scout, an independent listing site (not Mercor). The apply link may be a referral link.