ML Scientist - Adversarial Robustness - AI Trainer

Job Description

Job Description

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

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• For any help or support, reach out to: View email address on ziprecruiter.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.