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Face Recognition Jobs (NOW HIRING)

Xident B.V.

$140 - $190/hr

Senior Machine Learning Engineer We're looking for a Senior ML Engineer to advance our age bracket classifiers and face recognition models. We run 5 binary classifiers (+12/+15/+18/+21/+25) deployed ...

Downloadmoments

Senior iOS Engineer

Manhattan, NY · On-site

$100 - $150/hr

You'll work on on-device face recognition, photo pipeline optimization, and crafting a delightful user experience. This is a high-impact role where your work ships directly to users every week. What ...

Xident B.V.

Senior Machine Learning Engineer

Union, NJ · On-site

$140 - $190/hr

Senior Machine Learning Engineer We're looking for a Senior ML Engineer to advance our age bracket classifiers and face recognition models. We run 5 binary classifiers (+12/+15/+18/+21/+25) deployed ...

Pindrop

Research Scientist (Video)

Design, implement, and evaluate deep learning algorithms related to video processing, face recognition, and video deepfake detection. * Design, develop, and maintain internal research packages to ...

Pindrop

Research Scientist (Video)

Design, implement, and evaluate deep learning algorithms related to video processing, face recognition, and video deepfake detection. * Design, develop, and maintain internal research packages to ...

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Face Recognition information

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$55.5K

$119.9K

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How much do face recognition jobs pay per year?

As of Sep 7, 2026, the average yearly pay for face recognition in the United States is $119,854.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $134,000.00 per year, depending on experience, location, and employer.

What is a face recognition job?

A Face Recognition job typically involves working with facial recognition technology to develop, improve, or implement systems that can identify or verify individuals based on their facial features. Professionals in this field may work on machine learning models, data collection, algorithm optimization, or security applications. These roles are common in industries like security, law enforcement, biometrics, and artificial intelligence research. Skills in computer vision, deep learning, and data analysis are often required.

What are the key skills and qualifications needed to thrive in a face recognition position, and why are they important?

To excel in a Face Recognition role, you need strong expertise in computer vision, machine learning, and data analysis, typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools like Python, OpenCV, TensorFlow, and relevant certifications in AI or deep learning are highly beneficial. Strong problem-solving abilities, attention to detail, and effective collaboration make candidates stand out. These capabilities are vital for developing accurate, reliable face recognition solutions and ensuring their integration within larger security or authentication systems.

What are some typical challenges faced by professionals working in face recognition roles?

Professionals in face recognition roles often encounter challenges such as ensuring high accuracy with diverse datasets, addressing privacy concerns, and minimizing biases in algorithms. They must continually adapt to evolving regulations, stay updated with state-of-the-art models, and optimize systems for efficiency and scalability. Collaborating with multidisciplinary teams—including software developers, data scientists, and product managers—is common to align technical solutions with real-world applications. These challenges make the role dynamic, demanding, and rewarding for those passionate about advancing technology responsibly.

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Cities with the most Face Recognition job openings:

What are the most commonly searched types of Face Recognition jobs?

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What states have the most Face Recognition jobs?

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Face Recognition jobs near you
Infographic showing various Face Recognition job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 18% Part Time, and 2% Contract. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution, with an average salary of $119,854 per year, or $57.6 per hour.

Senior Machine Learning Engineer

Xident B.V.

On-site

$140 - $190/hr

Other

Posted 4 days ago

Job description

Senior Machine Learning Engineer

We're looking for a Senior ML Engineer to advance our age bracket classifiers and face recognition models. We run 5 binary classifiers (+12/+15/+18/+21/+25) deployed as ONNX models for client-side inference via WebAssembly — you'll improve accuracy, reduce bias, and tackle anti-spoofing.

Xident is building the future of digital identity verification. Our platform enables businesses to verify users' ages and identities in seconds, while respecting privacy through our unique "Verify Once, Access Everywhere" model.

Founded in 2023, we've already processed over 10M+ verifications processed and serve 500+ businesses. We're a remote-first company with team members across 12 countries.

Our mission is simple: To make identity verification seamless, private, and accessible for everyone. We believe privacy and convenience shouldn't be mutually exclusive, and we're proving it every day.

25+

Team members

500+ businesses

Customers

12

Countries

What You'll Do
  • 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
What We're Looking For
  • 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
Nice to Have
  • PhD in Computer Science, ML, or related field
  • Experience with document OCR and VLM-based verification
  • Background in privacy-preserving ML — on-device inference, no server-side face storage
Our Values

We iterate quickly, gather feedback, and improve continuously.

Ownership Mentality

Everyone owns their domain end-to-end. No finger-pointing, just solutions.

Transparent by Default

We're happy to answer any questions before you apply. Reach out to our team anytime.

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