Lead Machine Learning Engineer for Fraud ML (Hamilton)

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 Apply on Kit Job: kitjob.ca/job/2pssfc