ML Scientist - Adversarial Robustness
$100 - $120 per hourMercor
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 with limited data, compute, and model-size budgets.
- Enhance model robustness to adversarial inputs and conversations.
- Compress models to meet size and latency constraints without losing accuracy.
- Diagnose and resolve training issues effectively.
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 equivalent research track record through publications or impactful open-source contributions.
Preferred
- Experience in scaling laws and training-efficiency research .
- Knowledge of curriculum learning and data ordering.
- Skills in model evaluation , uncertainty estimation , and model calibration .
- Expertise in data augmentation and synthetic data for robustness.
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: 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.
Vacancy posted 12 days ago
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