Machine Learning Engineer

IDSentric is seeking a talented Machine Learning Engineer to join our AI team. In this role, you'll develop cutting-edge machine learning models that power our document verification, facial recognition, and fraud detection capabilities.

The Role

As a Machine Learning Engineer at IDSentric, you will:

Design, train, and optimize machine learning models for identity verification use cases
Develop computer vision algorithms for document authenticity verification
Create and improve facial recognition and liveness detection systems
Build fraud detection models that adapt to evolving threats
Collaborate with the engineering team to deploy models to production
Continuously evaluate and improve model performance
Stay up-to-date with the latest research and techniques in ML/AI

Current Projects You Could Work On

Here are some exciting projects our AI team is currently tackling:

Advanced document forgery detection using deep learning techniques
Next-generation facial liveness detection to prevent presentation attacks
Cross-document validation and data extraction with transformer models
Behavioral biometrics for continuous authentication
Anomaly detection systems for fraud prevention
Privacy-preserving machine learning with federated learning techniques

Research and Development Focus

In addition to product development, our ML team contributes to:

Publishing research papers in leading conferences and journals
Collaborating with academic institutions on cutting-edge research
Creating and contributing to open-source projects in the identity verification space
Participating in industry standards development for AI ethics and identity verification
Hosting and presenting at machine learning meetups and conferences

Requirements

MS or PhD in Computer Science, Machine Learning, or related field
At least 3 years of experience in ML/CV
Proficiency in Python and ML frameworks (TensorFlow, PyTorch)
Experience with computer vision and OCR technologies
Strong understanding of identity verification challenges
Experience deploying ML models to production environments
Excellent problem-solving skills and attention to detail

Nice to Have

Experience with facial recognition systems
Knowledge of document forensics or fraud detection
Experience with edge deployment of ML models
Publications in relevant ML/CV conferences or journals
Experience with MLOps tools and practices

Our AI Tech Stack

We currently work with:

Python for ML development
TensorFlow and PyTorch for deep learning
OpenCV for computer vision
AWS SageMaker for model training and deployment
DVC for ML versioning
MLflow for experiment tracking

What We Offer

Competitive salary and equity package
Remote-first work environment with flexible hours
Comprehensive health, dental, and vision benefits
Annual conference and learning stipend
Access to GPU resources for experimentation
Opportunity to solve challenging real-world problems
Collaborative team of AI enthusiasts