Machine Learning Engineer I (Fraud Risk Modeling)

Location: Palo Alto, California, United States

Annual salary: $90,000–$185,000

Company

hirify.global is a large auto insurer and member of the Berkshire Hathaway family, using artificial intelligence to protect customers from fraud and improve insurance operations.

What you will do

• Implement, test, and maintain machine learning models for fraud detection and risk assessment.
• Support feature engineering, data validation, experimentation, and the creation of training and inference datasets.
• Contribute to batch and near-real-time ML pipelines and assist with production model deployment through MLOps tooling.
• Monitor data quality, model performance, and system reliability.
• Write clean, tested, maintainable Python and/or Java code and participate in code reviews, design discussions, and post-incident reviews.
• Collaborate with data scientists, product managers, and senior ML engineers while following security, compliance, and governance standards.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• 1–3 years of hands-on experience building or supporting ML models or data pipelines; internships count.
• Proficiency in Python and familiarity with scikit-learn, PyTorch, or TensorFlow.
• Basic understanding of model training, evaluation, and deployment.
• Strong problem-solving skills and willingness to learn production ML systems.
• hirify.global will not sponsor a new applicant for employment authorization for this position.

Nice to have

• Experience or exposure to fraud detection, risk modeling, or anomaly detection.
• Familiarity with SQL and large-scale data platforms such as Spark or Snowflake.
• Experience with AWS, Azure, or containerized environments.
• Interest in responsible AI, model monitoring, and explainability.

Culture & Benefits

• Personalized development programs, mentorship, and certification assistance.
• Inclusive and collaborative culture focused on shared success.
• Competitive pay, benefits, and flexibility supporting employee well-being.
• Work in a regulated environment focused on innovation, security, compliance, and customer protection.