Deep Learning / AI Scientist - Liveness Detection and Biometrics

VIDA Digital Identity; Daerah Khusus Ibukota Jakarta; On-site; USD 30.000 - 50.000; Full time

Job summary

VIDA Digital Identity is seeking a passionate Deep Learning AI Scientist specializing in Liveness Detection and Biometrics. Your expertise will contribute to enhancing identity verification systems, making digital identity accessible for everyone. If you're driven to solve complex problems in a collaborative environment, join our mission.

Qualifications

• 3+ years of hands-on experience in deep learning model development for biometrics or liveness detection.
• Experience developing and deploying machine learning models in production.
• Familiarity with on-device inference for machine learning models is a plus.

Responsibilities

• Design, train, and deploy deep learning models for liveness detection.
• Collaborate with teams to deliver impactful solutions.
• Monitor and A/B test new model versions.

Skills

Deep understanding of modern computer vision techniques

Deep learning

Machine learning

Adversarial training

Problem solving

Collaboration in fast-moving environments

Education

Advanced degree in a quantitative field

Tools

Python

C++

Scala

Java

TensorFlow

PyTorch

MXNet

AWS

GCP

Azure

Job description

Our mission is to create innovative, robust, and user-friendly digital identity solutions. We are looking for a passionate and skilled Deep Learning AI Scientist specializing in Liveness Detection and Biometrics to join our dynamic team. Your work will directly impact the security and reliability of VIDA's identity verification systems.

Responsibilities:

1. Liveness Detection Development: Design, train, and deploy advanced deep learning models to ensure robust liveness detection, preventing spoofing attacks using photos, videos, masks, or other methods.

2. Design, train and deploy biometric models to correctly identify users.

3. Own the full lifecycle of deploying models: from data labelling, working with engineers to design scalable APIs, to monitoring and A/B testing new model versions.

4. Stay updated with the latest research in biometrics, computer vision, and deep learning, incorporating new techniques to improve VIDA’s products.

5. Collaborate with business, product, operations, and engineering teams to deliver impact for our customers.

6. Work independently or in a team to solve complex problem statements.

Requirements:

1. An advanced degree in a quantitative field, and 3+ years of hands-on experience in deep learning model development for biometrics or liveness detection or a similar field.

2. Deep understanding of modern computer vision techniques, deep learning, and machine learning.

3. Experience developing and deploying machine learning models in production.

4. Experience with adversarial training to enhance model robustness.

5. Proficient in Python, C++, Scala, or Java.

6. Familiarity with modern deep learning frameworks such as TensorFlow, PyTorch, MXNet.

7. Familiarity with cloud platforms like AWS, GCP, or Azure for model deployment.

8. Experience in on-device inference for machine learning models is a plus.

9. Take pride in ownership and driving projects to impact.

10. Thrive in a fast-moving collaborative environment.

What are we trying to solve?

We have 7.5 billion people on Earth, of which over 1 billion cannot securely prove their identity right now.

Every year, 140 million babies are born, of which 40 million go unregistered.

These people are deprived of social benefits, civil rights, and economic opportunities due to lack of proper identification. We believe this must change.

At VIDA, we are creating a frictionless digital identity system that is accessible to everyone, anywhere.

Why are we solving this problem?

The UN and World Bank's ID4D initiative aim to provide a legal identity to everyone by 2030. We want VIDA to be a pioneer in making digital identity a human right.

Who are we?

We are a driven team committed to solving this global issue for various personal and societal reasons, united by our goal to create equitable access to digital identity.