ML Scientist - Adversarial Robustness

About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: LLM Research Scientist (Pre-training & Computer Vision & Adversarial Robustness) Type: Contract Compensation: $100–$120/hour Location: Remote Role Responsibilities Train image classifiers and generative image models from scratch. Fine-tune open-weight language models . Optimize models for limited data, compute, and model-size budgets. Enhance model robustness against adversarial inputs and conversations. Compress models to meet size and latency constraints without losing accuracy. Diagnose and resolve training issues to improve model performance. Qualifications Must-Have 3+ years of machine learning research experience ( PhD research counts). 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. Preferred Experience with Adversarial Robustness and Efficient Computer Vision . Knowledge in Generative Image Modeling and LLM Post-Training & Behavioral Robustness . Experience in Multilingual Pre-training and additional areas like scaling laws and curriculum learning . Application Process (Takes 20–30 mins to complete) Upload resume AI interview based on your resume Submit form Resources & Support For details about the interview process and platform information, please check: For any help or support, reach out to: PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity. Originally posted on Himalayas