Staff/Principal Research Engineer
Tools for Humanity is a technology company building products for humans in the age of AI.
Maintainer signals as of 9/2/2026
About Tools for Humanity
Tools for Humanity develops hardware, software, and services connected to World, described as an open-source real-human network. Its products include the Orb for privacy-focused proof-of-human verification, World App for World ID access, digital asset management, wallet functionality, transactions, and Mini Apps, and World Spaces for verification, community programming, and events. The company serves end users and organizations seeking to integrate World infrastructure into their projects.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Join the AI & Biometrics team to build high-scale biometric recognition and fraud detection systems. The role covers deep learning and classical models, custom hardware and mobile deployment, scalable training pipelines, data collection, monitoring, and production refinement.
Requirements
- 5+ years of industry experience in computer vision, deep learning, and/or data science.
- MSc or PhD in computer science, data science, electrical engineering, or a related STEM field.
- Ability to conduct research and translate findings into practical applications.
- Extensive experience training, deploying, and iterating on production deep learning models.
- Advanced Python programming skills and experience with OpenCV, Pandas, NumPy, and Seaborn.
- Strong experience with PyTorch and its ecosystem.
- Familiarity with AWS, GCP, or Azure and NoSQL databases such as MongoDB, Elasticsearch, or Redis.
- Excellent English communication skills and ability to deliver under tight deadlines.
- Nice to have: deepfake or presentation attack detection, biometrics, embedded hardware, Rust, or research contributions.
Responsibilities
- Lead development of deep learning and classical algorithms for biometric recognition.
- Optimize models for deployment on custom hardware and mobile platforms.
- Build and maintain scalable, efficient model training pipelines.
- Oversee the full model lifecycle, including data collection, deployment, monitoring, and refinement.
- Deploy and iterate on production models to improve accuracy and robustness.
- Direct presentation attack detection and fraud prevention efforts.
Benefits
- Healthcare
- Dental
- Vision
- 401(k) plan and match
- Life insurance
- Flexible time off
- Commuter benefits
- Professional development stipend
- Competitive long term incentive package