Lead Machine Learning Engineer for Fraud ML

Become a Lead Machine Learning Engineer with Affirm's Fraud ML team, specializing in real-time fraud prevention systems. This remote position in Canada offers impactful challenges. As part of Affirm, you'll leverage your 6+ years of experience to construct and optimize machine learning models focused on fraud detection. Collaboratively engage with various teams to convert ideas into prototypes and production-ready solutions while improving operational efficiencies. Your leadership will help define best practices in model development amid evolving fraud patterns. Key Responsibilities:

• Spearhead the creation of fraud detection models
• Construct and scale feature pipelines using diverse data
• Drive the deployment of high-performing modeling solutions
• Monitor systems for reliability and operational integrity
• Streamline model building processes and workflows

Requirements:

• Minimum 6 years of experience with ML models
• Expertise in Python for writing production-ready code
• Background in classification and deep learning techniques
• Proficient in distributed data processing frameworks
• Familiarity with ML tools such as Kubeflow or Airflow

Lead the development of advanced fraud detection models that enhance security and customer trust at Affirm. #J-18808-Ljbffr