Staff Applied Research Engineer, Biometrics
New
V
VeriffIdentity verification
Location: Spain (Remote), USA (Remote)Full-TimeStaff
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years of experience in Applied Research or Data Science
- Required Skills
- PythonSQLBashOpenCVPyTorchTensorflowComputer Vision
Requirements
- 5+ years of experience in Applied Research or Data Science, with a proven track record of moving complex Computer Vision models from paper to production.
- Deep Mastery of CV Frameworks: Expert-level PyTorch or TensorFlow skills, specifically in implementing custom layers, loss functions, and domain-adversarial training loops.
- A "Physics-First" Intuition: Strong background in classical image processing (OpenCV) and 3D geometry; you understand why a 2D surface looks different than a 3D face to a sensor.
- Business & Production Acumen: You treat inference latency and compute cost as first-class constraints. You prefer an elegant, efficient solution over a "brute-force" ensemble.
- Strong Engineering Foundations: Proficient in Python, Bash, and SQL. You are comfortable building your own data pipelines and debugging containerized services.
- A skeptical, questioning approach: You don't take "SOTA" claims at face value. You investigate failure modes, hunt for bias, and demand empirical evidence before committing to a new direction.
Responsibilities
- Architecting the Research Pipeline: Building the infrastructure to reproduce and adapt SOTA papers within 4–6 week cycles, ensuring our models outpace the global fraud landscape.
- Engineering Physics-Based Defenses: Developing "attack-agnostic" features—leveraging optical flow, specular reflection, and 3D geometry—to exploit immutable physical laws that attackers cannot easily circumvent.
- Solving for Domain Heterogeneity: Implementing advanced Domain Adaptation and Generalization techniques to eliminate performance variance across device types (iOS vs. Android), demographics, and environmental conditions.
- Optimizing for SaaS Scale: Writing high-performance, maintainable Python code to ensure complex CV models remain cost-efficient and latency-optimized.
- Strategic Prototyping: Working from first principles to decide when a novel architecture is required versus when the solution lies in superior data curation or procedural attack generation.
View Full Description & ApplyYou'll be redirected to the employer's site
