Role Overview
We’re seeking a Data Scientist II to join our document verification team, focusing on computer vision and deep learning. In this individual contributor role, you'll design, refine, and maintain machine learning models that power systems analyzing identity documents. You'll take ownership of modeling initiatives and work closely with engineering and data science teams to improve accuracy, performance, and scalability.
Key Responsibilities
- Design, train, and optimize deep learning models for tasks including document classification, image quality evaluation, text field extraction, and fraud detection.
- Implement and assess modern neural network architectures such as convolutional networks and vision transformers, including multimodal variants.
- Own key components of end-to-end machine learning pipelines—from data curation and model training to evaluation and deployment.
- Conduct detailed error analysis and model diagnostics to identify performance bottlenecks and drive data-informed improvements.
- Participate in technical planning, code reviews, and the development of shared modeling standards across the team.
- Write clean, production-ready code and contribute to internal ML tools and infrastructure.
- Partner with engineering and product teams to ensure models align with product goals, latency requirements, and system reliability.
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience, with at least 5 years in machine learning or data science roles.
- Proficiency in Python and hands-on experience with deep learning frameworks like PyTorch or TensorFlow.
- Proven experience applying CNNs and other deep learning models in real-world computer vision applications, with familiarity in transformer-based vision systems.
- Solid grasp of machine learning principles, including model validation, overfitting prevention, regularization, and transfer learning techniques.
- Experience using Git, experiment tracking tools, and building reproducible modeling workflows.
- Clear communication skills and the ability to collaborate effectively across technical teams.
Preferred Qualifications
- Advanced degree (MS or PhD) in a relevant technical field is a plus.
Technical Environment
You’ll work with Python, PyTorch, TensorFlow, convolutional and transformer-based vision models, multimodal architectures, Git, and modern experiment tracking systems.
Company Culture
We hire individuals who thrive on ownership and initiative. Our environment favors fast-moving problem solvers who think critically and prioritize precision in delivering solutions. We value high performance and measurable impact, especially when it comes to solving real customer challenges. As an equal opportunity employer, we support diversity in all its forms and provide accommodations throughout the hiring process for candidates with disabilities.
