ML / Computer Vision Engineer (Face Geometry, CNNs, On-Device ML)

Company Description

ByoSync OS Layer is an advanced biometric authentication platform that replaces traditional OTPs and passwords with secure, real-time facial verification. Tailored for Indias dynamic digital ecosystem, ByoSync operates seamlessly on any smartphone, utilizing encrypted tokens to ensure that no biometric data is stored . The platform enables secure payments, identity access, and digital services through a single scan, delivering a fast, private, hardware-free , and security-first authentication experience.

Role Description

We are looking for a Machine Learning / Computer Vision Engineer with a strong mathematical foundation and experience building CNN-based vision systems .

This is a fixed-term role for 2 months , with the opportunity to convert to a full-time position based on performance and business requirements.

You will work on face representation, geometric processing, normalization, model training, evaluation, and on-device optimization , contributing directly to production-grade ML systems deployed on resource-constrained devices.

What Youll Work On

• Design face representation and processing pipelines using geometry, linear algebra, and statistical modeling
• Develop robust normalization and alignment techniques across pose, scale, and illumination variations
• Build and train CNN-based models for face representation and liveness detection
• Formulate matching, scoring, and confidence estimation algorithms
• Create evaluation frameworks including accuracy, error rates, latency, and device-level analysis
• Optimize models for on-device execution , including:
• Quantization, pruning, and distillation
• Memory, latency, and power constraints
• Collaborate with mobile engineers to ensure real-time, production-ready inference

Qualifications

• Strong background in Computer Vision, Machine Learning, or Applied Mathematics
• Deep understanding of CNN architectures and representation learning
• Excellent grasp of linear algebra, probability, and optimization
• Experience designing custom normalization, alignment, or feature extraction pipelines
• Proficiency in Python and PyTorch (or similar frameworks)
• Experience training and validating models on real-world data

Nice to Have

• Experience with face analysis systems (recognition, liveness, identity verification)
• Knowledge of model compression and deployment on constrained devices
• Exposure to robust or security-sensitive ML systems
• Experience in fintech, identity, or other regulated domains