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Face Recognition Jobs (NOW HIRING)

Pindrop

Research Scientist II

... face recognition, and video deepfake detection. • Design, develop, and maintain internal research packages to train and test ML models, ensuring absolute reproducibility and computational ...

Pindrop

Research Scientist II (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 ...

The Fedcap Group

Teacher Assistant (Temporary)

Bronx, NY · On-site

$17 - $22/hr

Assure children transfer safely withing the building and to the playground and back- maintaining face recognition procedures at all times * Utilize PBIS and social/emotional learning strategies with ...

The Fedcap Group

Teacher Assistant (Summer)

Bronx, NY · On-site

$17 - $22/hr

Assure children transfer safely withing the building and to the playground and back- maintaining face recognition procedures at all times * Utilize PBIS and social/emotional learning strategies with ...

Easterseals

Teacher Assistant (Temporary)

New York, NY

$17 - $22/hr

Assure children transfer safely withing the building and to the playground and back- maintaining face recognition procedures at all times * Utilize PBIS and social/emotional learning strategies with ...

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Face Recognition information

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How much do face recognition jobs pay per year?

As of Jul 3, 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.

Which 3 jobs will survive AI?

Face recognition jobs, such as biometric analysts and security personnel, are likely to persist because they require human oversight, ethical judgment, and handling complex situations AI cannot fully replicate. Roles involving creative thinking, emotional intelligence, and complex problem-solving, like psychologists or creative professionals, are also expected to remain relevant. Technical skills in AI management and cybersecurity will continue to be in demand as AI technology advances.

What are the key skills and qualifications needed to thrive in the 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.

How to work face recognition?

A face recognition job involves developing or implementing algorithms that identify or verify individuals based on facial features. It requires skills in computer vision, machine learning, and programming languages like Python, along with familiarity with tools such as OpenCV or deep learning frameworks. Proper data handling, model training, and testing are essential steps in the process.

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 jobs pay $4000 a week without a degree?

In the field of face recognition, high-paying roles such as biometric technician, facial recognition software developer, or AI specialist can sometimes reach or exceed $4,000 weekly, especially with specialized skills and experience. These roles often require expertise in machine learning, programming, and image analysis, and may involve working in tech companies or security firms without a formal degree but with relevant certifications or training.

Can you get a job as a super recogniser?

Super recognisers are individuals with exceptional facial recognition abilities, often identified through specialized testing. While they are not typically employed as standard roles, some law enforcement agencies and security organizations may hire or train individuals with these skills for tasks like surveillance and suspect identification. Formal employment opportunities are limited and usually require relevant experience or training in security or law enforcement fields.
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What are the most commonly searched types of Face Recognition jobs? The most popular types of Face Recognition jobs are:
What states have the most Face Recognition jobs? States with the most job openings for Face Recognition jobs include:
What job categories do people searching Face Recognition jobs look for? The top searched job categories for Face Recognition jobs are:
Face Recognition jobs near you
Infographic showing various Face Recognition job openings in the United States as of June 2026, with employment types broken down into 60% Full Time, and 40% Part Time. Highlights an 100% In-person job distribution, with an average salary of $119,854 per year, or $57.6 per hour.
Research Scientist II

Research Scientist II

Pindrop

Remote

Full-time

Posted yesterday

Job description

Job Summary:
Pindrop is the Real Human + Right Human® Identity Trust Platform for the AI era, focused on delivering continuous identity verification and deepfake detection. The Research Scientist II will drive core research initiatives, develop functionalities for real-time video processing, and translate machine learning models into product solutions.
Responsibilities:
• Conduct research to develop new functionalities and improve existing technologies for real-time video processing and meeting analytics.
• 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 train and test ML models, ensuring absolute reproducibility and computational efficiency.
• Partner closely with research engineers and engineering teams to help deploy research models and tools into production environments.
• Participate in cross-functional team meetings, contribute to regular research and code reviews, and publish patents and peer-reviewed papers in top computer vision, audio, and speech conferences.
Qualifications:
Required:
• PhD in a quantitative field (e.g., Computer Science, Mathematics, Engineering, Artificial Intelligence) or equivalent industry research experience.
• 3+ years of professional experience in Deep Learning, specifically applied to computer vision, face recognition, video deepfake detection, or general machine learning.
• Strong programming proficiency in Python with a proven ability to design, develop, and maintain research packages to train and test ML models.
• Hands-on mastery of modern machine learning frameworks such as PyTorch, TensorFlow, or Keras.
• A proven track record of successful, timely project delivery and the ability to contribute to patents and peer-reviewed publications.
Preferred:
• Functional programming experience in C/C++ or working knowledge of deployment environments using Go, TF-Lite, and TF-Micro.
• Practical experience with real-time video processing pipelines and video data acquisition/preparation tasks.
• Foundational domain knowledge of biometrics, identity authentication, fraud patterns, or consumer security concepts.
Company:
Pindrop uses AI-based IVR authentication and anti-fraud solutions to increase efficiency in call centers and stop fraudulent transactions. Founded in 2011, the company is headquartered in Atlanta, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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