TalentAQ

TalentAQ

AI/ML Engineer

EngineeringFull Time

Required Skills
1 skills

risk & anomaly detection

Job Description

<h3>Job Overview</h3><p>We are looking for an AI/ML Engineer to join our team and help build TrustNet, a platform dedicated to eliminating scams and fraud in crypto and forex trading. As an AI/ML Engineer, you will develop and implement machine learning models for risk and anomaly detection, contributing to the creation of a safer trading environment for millions of users.</p><h3>Key Responsibilities</h3><ul><li>Develop and deploy machine learning models for fraud detection.</li><li>Design and implement algorithms for risk assessment and anomaly detection.</li><li>Analyze large datasets to identify patterns and trends.</li><li>Collaborate with engineers to integrate AI solutions into the TrustNet platform.</li><li>Stay up-to-date with the latest advancements in AI and machine learning.</li></ul><h3>Required Skills</h3><ul><li>Strong background in machine learning and statistical modeling.</li><li>Experience with risk and anomaly detection techniques.</li><li>Proficiency in programming languages such as Python.</li><li>Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch).</li></ul>

Job Overview

We are looking for an AI/ML Engineer to join our team and help build TrustNet, a platform dedicated to eliminating scams and fraud in crypto and forex trading. As an AI/ML Engineer, you will develop and implement machine learning models for risk and anomaly detection, contributing to the creation of a safer trading environment for millions of users.

Key Responsibilities

  • Develop and deploy machine learning models for fraud detection.
  • Design and implement algorithms for risk assessment and anomaly detection.
  • Analyze large datasets to identify patterns and trends.
  • Collaborate with engineers to integrate AI solutions into the TrustNet platform.
  • Stay up-to-date with the latest advancements in AI and machine learning.

Required Skills

  • Strong background in machine learning and statistical modeling.
  • Experience with risk and anomaly detection techniques.
  • Proficiency in programming languages such as Python.
  • Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch).

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