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.