Machine Learning Engineer (Computer Vision)

TL;DR

Machine Learning Engineer (Computer Vision): Developing and optimizing biometric identification and anti-spoofing systems for the World Network with an accent on face verification, uniqueness detection, and on-device performance. Focus on building evaluation pipelines, iterating on deep learning architectures, and implementing pragmatic CV solutions for real-world conditions.

Location: On-site in Munich

Company

hirify.global designs and builds the technology behind World, a global human network utilizing iris and face recognition for privacy-preserving identity verification.

What you will do

• Own face ML projects end-to-end, from initial problem definition to production validation and monitoring.
• Iterate on deep learning architectures, losses, and data pipelines for biometric identification and anti-spoofing.
• Implement classical CV and image processing solutions to ensure efficiency and reliability.
• Design robust evaluation pipelines to catch model regressions before they reach production.
• Analyze face datasets to identify failure modes and drive model and evaluation changes.
• Collaborate with MLOps and Mobile teams to meet strict latency and memory budgets for on-device deployment.

Requirements

• Significant experience training and shipping deep learning systems for computer vision.
• Strong proficiency in Python and a modern framework such as PyTorch.
• Solid foundations in classical CV with experience using OpenCV and NumPy.
• Expertise in designing production-grade evaluations, including metric selection and regression analysis.
• Ability to write maintainable research and production-quality code.
• Location: Must be based in or be able to work on-site in Munich

Nice to have

• Direct experience with biometric verification, liveness detection, or adversarial ML systems.
• Knowledge of edge optimization, quantization, pruning, and distillation for on-device deployment.
• Proficiency in Rust for high-performance code paths.
• Background in sensors, imaging, or camera ISPs.

Culture & Benefits

• Opportunity to work with an elite team from OpenAI, Tesla, SpaceX, and Google.
• Contribution to a product operating at a global scale with over 17 million verified users.
• Pragmatic engineering culture that balances deep learning with efficient classical methods.
• Ownership-driven environment focusing on end-to-end delivery and scientific rigor.