About the Role
Join a small team building AI technology for synthetic media detection, media forensics, and digital fraud prevention. This role combines rigorous research with hands-on engineering, helping turn promising methods into reliable software for practical digital trust and security challenges.
What You’ll Do

• Investigate methods for synthetic media detection, media analysis, and fraud prevention.

• Read, assess, and reproduce relevant research, then identify approaches for further development.

• Design experiments, establish baselines, and evaluate model performance on realistic data.

• Implement research ideas and collaborate with engineering to bring effective approaches into production.

• Analyze failure cases and improve model reliability, generalization, and computational efficiency.

• Document methods and findings, contribute to research papers and technical writing, and help prioritize work around practical problems.

What We’re Looking For

• Strong foundations in machine learning, experimental design, and model evaluation.

• Experience building, training, and evaluating models with modern machine learning tools.

• A demonstrated ability to translate research into working software and ship production code.

• Ability to critically read research papers, design experiments, and clearly communicate methods and findings.

• Evidence of research and engineering ability through shipped systems, publications, open-source work, or substantial applied projects.

• Experience in computer vision, audio processing, multimodal learning, media forensics, adversarial robustness, or deployment under real-world latency and reliability constraints is valuable.

• Comfort taking ownership of open-ended problems in a small team.

Compensation & Benefits
Compensation is discussed during the hiring process. Visa sponsorship is available.
Location
Remote.

About the Role
Join a small team building AI technology for synthetic media detection, media forensics, and digital fraud prevention. This role combines rigorous research with hands-on engineering, helping turn promising methods into reliable software for practical digital trust and security challenges.
What You’ll Do

• Investigate methods for synthetic media detection, media analysis, and fraud prevention.

• Read, assess, and reproduce relevant research, then identify approaches for further development.

• Design experiments, establish baselines, and evaluate model performance on realistic data.

• Implement research ideas and collaborate with engineering to bring effective approaches into production.

• Analyze failure cases and improve model reliability, generalization, and computational efficiency.

• Document methods and findings, contribute to research papers and technical writing, and help prioritize work around practical problems.

What We’re Looking For

• Strong foundations in machine learning, experimental design, and model evaluation.

• Experience building, training, and evaluating models with modern machine learning tools.

• A demonstrated ability to translate research into working software and ship production code.

• Ability to critically read research papers, design experiments, and clearly communicate methods and findings.

• Evidence of research and engineering ability through shipped systems, publications, open-source work, or substantial applied projects.

• Experience in computer vision, audio processing, multimodal learning, media forensics, adversarial robustness, or deployment under real-world latency and reliability constraints is valuable.

• Comfort taking ownership of open-ended problems in a small team.

Compensation & Benefits
Compensation is discussed during the hiring process. Visa sponsorship is available.
Location
Remote.