Applied AI Researcher

About the Role

Join a small research and engineering team at a digital trust and security company. You will investigate methods for detecting synthetic media and digital fraud, then help translate effective research into production software.

What You'll Do

• Investigate AI methods for synthetic media detection, media forensics, and fraud prevention.
• Read and reproduce research, then assess which approaches are worth pursuing.
• Design experiments, establish baselines, and evaluate models on realistic data.
• Implement research ideas and collaborate with engineering to bring successful approaches into production.
• Analyze failure cases and improve model reliability, generalization, and computational efficiency.
• Document methods and findings, contribute to technical writing, and prioritize research around practical needs.

What We're Looking For

• At least 3 years of experience training deep learning models in PyTorch, including taking at least one model from concept to production.
• An MS or PhD in computer science, electrical engineering, or a related field, or equivalent research experience.
• Strong machine learning foundations and experience building, training, and evaluating models.
• Computer vision knowledge, including CNNs and vision transformers, and the tradeoffs between them at small parameter counts.
• Experience in at least one relevant area: synthetic media detection, image or video forensics, audio spoofing detection, generative models, or adversarial robustness.
• Ability to critically assess research papers, design experiments, communicate findings clearly, and turn research into shipped software.
• Evidence of research and engineering ability through production systems, publications, open-source work, or substantial applied projects.

Compensation & Benefits

Base salary is flexible based on experience and candidacy. The package includes a performance bonus and 0.25% to 1% equity. Visa sponsorship is available.

Location

On-site in New York, New York, United States.

Originally posted on Himalayas