Data Scientist II - Computer Vision

Socure • Carson City, NV

2d

About The Position

Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day. We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading. About the Role We are seeking a Data Scientist II with strong experience in computer vision and deep learning to join our document verification team. This role is intended for an experienced individual contributor who can work independently on production ML models, own well-scoped modeling initiatives, and contribute to technical decision-making—while partnering closely with senior data scientists and engineers. You will help build and improve ML systems that analyze identity and document images at scale and play an active role in evolving our modeling approaches and infrastructure.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience, with 5 years or equivalent of professional experience in machine learning or data science.
• Strong proficiency in Python and hands-on experience with ML frameworks such as PyTorch or TensorFlow.
• Solid experience applying deep learning models (especially CNNs) in real-world computer vision systems, with working knowledge of transformer-based approaches.
• Strong understanding of model evaluation, experimentation, and ML fundamentals, including overfitting, regularization, and transfer learning.
• Experience with version control (Git), experiment tracking, and reproducible ML workflows.
• Ability to communicate technical ideas clearly and work effectively in a cross-functional team.

Nice To Haves

• MS or Ph.D is a plus.

Responsibilities

• Develop, maintain, and improve machine learning models for document verification use cases such as document classification, image quality assessment, field extraction, and fraud detection.
• Independently implement and evaluate deep learning architectures, including CNNs and transformer-based vision or multimodal models..
• Own well-defined components of end-to-end ML pipelines, including data preparation, model training, evaluation, and deployment to production.
• Perform in-depth error analysis, model diagnostics, and performance optimization, and propose data- or model-driven improvements.
• Contribute to technical design discussions, code reviews, and modeling best practices across the team.
• Write production-quality, maintainable code and contribute to shared ML tooling and infrastructure.
• Collaborate with engineering and product partners to ensure models meet product, performance, and reliability requirements.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 101-250 employees