About the role
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.