LLM Research Scientist – Pre-training, Computer Vision, Adversarial Robustness

Mercor

. Train image classifiers and generative image models from scratch .

Posted 10/17/2026contractRemote • United StatesMid-LevelSenior💰 $100 - $120 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in training and optimizing machine learning models, particularly in adversarial robustness and generative image modeling. Proficient in utilizing frameworks like PyTorch and TensorFlow to conduct impactful research and collaborate on advanced AI projects.

Highest-signal resume keywords

Machine Learning Research ExperienceProficiency in PyTorch, JAX, TensorFlowExpertise in Adversarial RobustnessExperience with Generative Image ModelingModel Compression and Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Image Classifier TrainingGenerative Image ModelsModel OptimizationAdversarial TrainingSupervised Fine-TuningDiffusion ModelsGANsVAEsCross-Lingual Data BalancingRobust-Accuracy Evaluation

Industry Keywords

AI ResearchMachine LearningRobustness-Accuracy Trade-OffsMultilingual ModelsData Augmentation

Tech Stack

Tools & technologies

PyTorchTensorflow

About the role

Key responsibilities & impact

Train image classifiers and generative image models from scratch
Fine-tune open-weight language models
Optimize models within limited data, compute, and model-size budgets
Improve robustness against adversarial inputs and adversarial conversations
Compress models to meet strict size and latency constraints while preserving accuracy
Diagnose and resolve training issues
Conduct empirical, open-ended machine learning research
Collaborate with leading AI researchers on challenging, high-impact projects
Work on projects training and enhancing frontier AI systems

Requirements

What you’ll need

3+ years of machine learning research experience; PhD research counts toward this requirement
Strong experience with PyTorch, JAX, TensorFlow, or similar ML frameworks
Degree from a top-100 university, experience at a FAANG or comparable AI company, or an equivalent research track record through publications or impactful open-source contributions
Expertise in one or more of: adversarial robustness, efficient computer vision, generative image modeling, LLM post-training and behavioral robustness, or multilingual pre-training
Experience with adversarial training of image classifiers, robust-accuracy evaluation, threat models, and robustness–accuracy trade-offs
Experience training image classifiers end-to-end, model compression, and deployment under hard size or latency budgets
Experience training diffusion models, GANs, VAEs, or flow-based generative models from scratch
Experience with supervised fine-tuning, DPO, RLHF, RLAIF, synthetic data generation, noisy or weak supervision, and rejection sampling
Experience shaping conversational behavior, including resistance to persuasion and sycophancy, calibrated confidence, and accepting corrections
Experience training multilingual or low-resource-language models from scratch, tokenizer design, and cross-lingual data balancing
Experience in scaling laws, curriculum learning, model evaluation, uncertainty estimation, calibration, data augmentation, or synthetic data for robustness is a plus
Must be able to work as an independent contractor
Mercor cannot support H1-B or STEM OPT candidates at this time

Benefits

Comp & perks

Flexible, project-based work
Competitive compensation
Fully remote work
Work on your own schedule
Weekly payments via Stripe or Wise
Projects may be extended, shortened, or concluded early depending on needs and performance
Reasonable accommodations upon request
Referral payments of up to $480 for each successful referral, subject to limits