Senior Machine Learning Engineer/Scientist (Fraud Detection)

Location: Seattle, Washington, United States; in-office expectation of at least 50% of the time, typically three days per week

Salary: $196,000–$245,000 starting base salary annually, plus equity and additional compensation components

Company

hirify.global provides secure financial services for customers sending, managing, and moving money across borders.

What you will do

• Design, build, and own machine learning models and systems that identify risky transactions and behavior in production.
• Advance fraud modeling with graph-based methods, sequence models, semi-supervised learning, and anomaly detection.
• Design offline and online evaluations that address class imbalance, delayed and censored labels, selective labeling bias, and adversarial drift.
• Take models from experimentation through production while meeting real-time latency, reliability, and monitoring requirements.
• Raise the team's scientific standards through experiment reviews, model deep-dives, mentoring, and applied research.
• Collaborate with data scientists, risk operations, and business stakeholders to identify emerging fraud patterns.

Requirements

• Degree in computer science, machine learning, statistics, or a related quantitative field, or equivalent experience.
• 5+ years of experience building and deploying machine learning systems, including taking novel approaches from idea to production.
• Strong machine learning fundamentals and experimental design skills, including evaluation under distribution shift.
• 5+ years of programming experience in Python or an equivalent language.
• Hands-on experience with modern machine learning frameworks such as PyTorch, XGBoost, LightGBM, or scikit-learn.
• Experience working with cloud platforms such as AWS, GCP, or Azure.

Nice to have

• Experience in fraud, risk, abuse, trust and safety, or another adversarial machine learning domain.
• Publications, patents, or open-source research contributions with applied research impact.
• Expertise in graph machine learning, sequence or behavioral modeling, anomaly detection, causal inference, or LLM applications to risk.

Culture & Benefits

• Connected Work Culture focused on in-person collaboration and regular office overlap.
• Flexible paid time off.
• Health, dental, and vision insurance with a 401(k) plan and company matching.
• Paid parental, medical, military, and family care leave.
• Mental health and family-forming benefits, employee stock purchase plan, and continuing education.