ML Scientist - Adversarial Robustness

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.

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.

Pay

$100–$120/hour

Type: Contract
Location: Remote