Senior ML Engineer — Edge CV & Face Recognition (Remote)

Xident B.V.; Union, Northern (NJ, KY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Xident B.V. seeks a Senior Machine Learning Engineer to advance age-bracket classifiers and on-device face recognition models. You will enable client-side inference via ONNX and WebAssembly to enhance privacy while maintaining performance.

Join a remote-first team, collaborating with Python and Go engineers on training pipelines and model deployment. This role emphasizes fairness, bias mitigation, and state-of-the-art CV techniques like ArcFace.

Qualifications

• 7+ years of machine learning experience with focus on computer vision.
• Deep expertise in face recognition architectures (ArcFace, CosFace, or similar).
• Strong PyTorch skills with experience exporting to ONNX for edge deployment.
• Published research or significant contributions to CV/ML projects.
• Experience with model optimization (quantization, pruning, distillation) for edge inference.
• Understanding of ML fairness, bias detection, and mitigation strategies.

Responsibilities

• Improve our age bracket binary classifiers — currently +18 achieves 0.03% FPR / 11% FRR, target similar for +12/+15/+21/+25
• Research and implement state-of-the-art face recognition using InsightFace (ArcFace) architectures
• Develop robust liveness detection and anti-spoofing models resistant to photos, videos, and deepfakes
• Optimize models for client-side ONNX Runtime inference (WebAssembly, Core ML, TensorFlow Lite)
• Build fair and unbiased models — measure and mitigate demographic performance gaps
• Collaborate with Python and Go engineers on training pipelines and model deployment via River queue

Skills

Machine learning

Computer vision

Face recognition

PyTorch

ONNX

Fairness & bias detection

Tools

ArcFace/CosFace architectures

ONNX Runtime

WebAssembly

River queue

Core ML

TensorFlow Lite

Job description

Xident B.V. seeks a Senior Machine Learning Engineer to advance age-bracket classifiers and on-device face recognition models. You will enable client-side inference via ONNX and WebAssembly to enhance privacy while maintaining performance.

Join a remote-first team, collaborating with Python and Go engineers on training pipelines and model deployment. This role emphasizes fairness, bias mitigation, and state-of-the-art CV techniques like ArcFace.