Data Scientist, Face Biometrics

Jobtailor; Dublin; On-site; EUR 70,000 - 100,000; Full time

Job summary

Jobtailor is seeking a skilled ML researcher to develop face authentication algorithms in Dublin. You will research and prototype methods for presentation attack detection and fraud prevention, and translate results into deployable models and policies.

The role requires hands-on work with PyTorch or TensorFlow, strong Python/C++ skills, and experience handling large datasets to meet performance and accuracy standards.

Qualifications

• Hands on experience in at least two of the areas listed below.

Responsibilities

• Developing machine learning algorithms for face authentication solutions.
• Researching, prototyping, and evaluating presentation attack detection and fraud prevention methods.
• Testing and configuring face algorithms to meet performance and accuracy standards.
• Running rigorous experiments, interpreting findings, and translating outcomes into deployable models and policies.

Skills

Machine Learning

Computer Vision

Deep Learning Frameworks

Python

C++

Data Preprocessing

Image Recognition

Liveness Detection

Anti-Spoofing

Experimental Methods

Education

Bachelor's/Master's/PhD in CS/EE/Math or related field

Tools

PyTorch

TensorFlow

Job description

• Developing machine learning algorithms for face authentication solutions
• Researching, prototyping, and evaluating presentation attack detection and fraud prevention methods
• Testing and configuring face algorithms to meet performance and accuracy standards
• Running rigorous experiments, interpreting findings, and translating outcomes into deployable models and policies

Requirements

• Hands on experience in at least two of the areas listed below:
• Computer Vision & Deep Learning
• Proficiency with deep learning frameworks such as PyTorch or TensorFlow
• Strong programming skills in Python and/or C++
• Data & Experimental Methods
• Experience handling, preprocessing, and analysing large-scale datasets
• Image Recognition & Matching
• Liveness & Anti-Spoofing
• Bachelors, Masters, or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field is preferred.

Core Competencies

Demonstrates expertise in developing machine learning algorithms for face authentication, with a strong focus on computer vision, deep learning, and data analysis. Proficient in utilizing frameworks like PyTorch and TensorFlow to create and evaluate robust models for liveness detection and anti-spoofing.

Highest-signal resume keywords

• Machine Learning Algorithms
• Computer Vision
• Deep Learning Frameworks
• Python Programming
• Data Analysis

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Computer Vision
• Deep Learning
• Python
• C++
• Data Preprocessing
• Image Recognition
• Liveness Detection
• Anti-Spoofing
• Experimental Methods

Industry Keywords

• Face Authentication
• Fraud Prevention
• Presentation Attack Detection
• Large-Scale Datasets
• Performance Standards

Tools & Technologies

• PyTorch
• TensorFlow