Biometric Data Annotator | Reviewer | Data Quality
About Keyo
We are building a company that reflects the world in which we want to live. One where we can enjoy the convenience of biometrics without compromising our privacy or personal freedom. To make this a reality, our technology allows businesses of all kinds to adopt biometric authentication quickly and easily. With Keyo, people are clocking into work, paying for a coffee, and unlocking doors with a wave of their hand. Our team is remote first, by design. Our talented employees work from all over the world because we want Keyo to reflect the people who use it: global citizens who bring their diverse perspectives to solve unique problems.
We are at an exciting juncture and looking for new voices and ideas to continue building our vision for the company. Keyo believes that the things that make us unique are our greatest strengths. We have an inclusive, global, remote-first workplace that comprises people from all different lifestyles, backgrounds, abilities, and nationalities.
Please note: Keyo is undergoing SOC2 compliance, performs background checks, and provides security training to team members.
We are looking for a Data Quality Assurance to join our Biometric Team. The ideal candidate will play a crucial role in ensuring high quality datasets for training and evaluating our biometric models. You will be responsible for reviewing, labeling, and categorizing biometric scans (RGB, IR) and identifying rejected scans, spoofs, duplicates, and IRspecific data. Additionally, you will assist in generating datasets under specific conditions to enhance model robustness.
Responsibilities
• Label biometric scans (RGB and IR), including rejected scans, spoofs, and duplicate enrollments.
• Review and validate image data, ensuring high quality and accurate annotations for machine learning training.
• Assist in testing new biometric releases and evaluating their performance.
• Support data collection efforts, including capturing scans in various lighting and environmental conditions.
• Collaborate with ML engineers and researchers to refine annotation guidelines and dataset quality.
• Maintain detailed documentation of labeling criteria, dataset variations, and identified issues.
Requirements
• Prior experience in data annotation, image labeling, or biometric data review.
• Strong attention to detail and the ability to identify patterns in biometric data.
• Familiarity with image analysis tools and annotation platforms.
• Basic understanding of computer vision and machine learning concepts (preferred but not mandatory).
• Ability to work independently and collaborate with teams remotely.
• Strong organizational skills and ability to handle large datasets.
Nice to Have:
• Experience working with biometric systems (e.g., fingerprint, face, palm, or iris recognition).
• Understanding of spoof detection techniques in biometrics.
• Exposure to Python and OpenCV for image processing (bonus).
• Knowledge of data quality assessment techniques.
Qualifications:
• 1+ years of experience in data annotation, labeling, or biometric data analysis.
• Bachelor's degree in a relevant field (computer science, data science, or related) is preferred but not required.
• Demonstrated ability to work with image datasets and follow detailed annotation guidelines.
If you read all the way to the end please start your application with the word banana to ensure that we know that you know what we are looking for.
Confidence Gap
We know the confidence gap and imposter syndrome can prevent us from meeting spectacular candidates, so please don't hesitate to apply—we'd love to hear from you.
Disqualification Statement
As a privacy-focused company, we hold privacy in the highest regard. All communications related to your candidacy will happen directly through our hiring team. Anyone who attempts to reach out to our team members through personal channels (such as social medial, personal email, or phone) will be automatically disqualified. Thank you for understanding.
Equal Employment Opportunity Employer
We are proud to be a global team united by diverse perspectives, cultures, and experiences. Our commitment to inclusion and respect extends across every border, embracing the unique contributions that individuals bring from all walks of life and every corner of the world. We are an equal opportunity employer and welcome everyone, regardless of race, color, religion, gender, gender identity, sexual orientation, age, national origin, disability, veteran status, or any other characteristic that makes you uniquely you. Your story matters, and we value the richness it adds to our shared journey We strive to create an environment where every team member—no matter where they are in the world—feels seen, heard, and empowered to succeed. From hiring to development, promotions, and beyond, we are dedicated to ensuring equity and fairness for all.
Together, we are building a global community where collaboration and respect drive innovation and belonging.
Please refer to our Privacy Policy to understand how we process your data. By applying for this position, you acknowledge and agree to the collection, processing, and storage of your personal data as outlined in the policy.
Apply Now
Apply Now
We are building a company that reflects the world in which we want to live. One where we can enjoy the convenience of biometrics without compromising our privacy or personal freedom. To make this a reality, our technology allows businesses of all kinds to adopt biometric authentication quickly and easily. With Keyo, people are clocking into work, paying for a coffee, and unlocking doors with a wave of their hand. Our team is remote first, by design. Our talented employees work from all over the world because we want Keyo to reflect the people who use it: global citizens who bring their diverse perspectives to solve unique problems.
We are at an exciting juncture and looking for new voices and ideas to continue building our vision for the company. Keyo believes that the things that make us unique are our greatest strengths. We have an inclusive, global, remote-first workplace that comprises people from all different lifestyles, backgrounds, abilities, and nationalities.
Please note: Keyo is undergoing SOC2 compliance, performs background checks, and provides security training to team members.
We are looking for a Data Quality Assurance to join our Biometric Team. The ideal candidate will play a crucial role in ensuring high quality datasets for training and evaluating our biometric models. You will be responsible for reviewing, labeling, and categorizing biometric scans (RGB, IR) and identifying rejected scans, spoofs, duplicates, and IRspecific data. Additionally, you will assist in generating datasets under specific conditions to enhance model robustness.
Responsibilities
• Label biometric scans (RGB and IR), including rejected scans, spoofs, and duplicate enrollments.
• Review and validate image data, ensuring high quality and accurate annotations for machine learning training.
• Assist in testing new biometric releases and evaluating their performance.
• Support data collection efforts, including capturing scans in various lighting and environmental conditions.
• Collaborate with ML engineers and researchers to refine annotation guidelines and dataset quality.
• Maintain detailed documentation of labeling criteria, dataset variations, and identified issues.
Requirements
• Prior experience in data annotation, image labeling, or biometric data review.
• Strong attention to detail and the ability to identify patterns in biometric data.
• Familiarity with image analysis tools and annotation platforms.
• Basic understanding of computer vision and machine learning concepts (preferred but not mandatory).
• Ability to work independently and collaborate with teams remotely.
• Strong organizational skills and ability to handle large datasets.
Nice to Have:
• Experience working with biometric systems (e.g., fingerprint, face, palm, or iris recognition).
• Understanding of spoof detection techniques in biometrics.
• Exposure to Python and OpenCV for image processing (bonus).
• Knowledge of data quality assessment techniques.
Qualifications:
• 1+ years of experience in data annotation, labeling, or biometric data analysis.
• Bachelor's degree in a relevant field (computer science, data science, or related) is preferred but not required.
• Demonstrated ability to work with image datasets and follow detailed annotation guidelines.
If you read all the way to the end please start your application with the word banana to ensure that we know that you know what we are looking for.
Confidence Gap
We know the confidence gap and imposter syndrome can prevent us from meeting spectacular candidates, so please don't hesitate to apply—we'd love to hear from you.
Disqualification Statement
As a privacy-focused company, we hold privacy in the highest regard. All communications related to your candidacy will happen directly through our hiring team. Anyone who attempts to reach out to our team members through personal channels (such as social medial, personal email, or phone) will be automatically disqualified. Thank you for understanding.
Equal Employment Opportunity Employer
We are proud to be a global team united by diverse perspectives, cultures, and experiences. Our commitment to inclusion and respect extends across every border, embracing the unique contributions that individuals bring from all walks of life and every corner of the world. We are an equal opportunity employer and welcome everyone, regardless of race, color, religion, gender, gender identity, sexual orientation, age, national origin, disability, veteran status, or any other characteristic that makes you uniquely you. Your story matters, and we value the richness it adds to our shared journey We strive to create an environment where every team member—no matter where they are in the world—feels seen, heard, and empowered to succeed. From hiring to development, promotions, and beyond, we are dedicated to ensuring equity and fairness for all.
Together, we are building a global community where collaboration and respect drive innovation and belonging.
Please refer to our Privacy Policy to understand how we process your data. By applying for this position, you acknowledge and agree to the collection, processing, and storage of your personal data as outlined in the policy.
Apply Now
Apply Now