Fraud ML Engineer — Production Models for Risk & Growth

Fdetimes; New York (NY); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Flexible PTO

Health and wellness stipend

Weekly coffee stipend

Relocation assistance to NYC or SF

Job summary

Ramp seeks a leader to drive the future of fraud machine learning. You will design data architectures, build core ML models, and set strategic roadmaps to mitigate fraud while minimizing friction for legitimate users.

You will work closely with product and engineering on model design, implementation, execution, and analysis. You will partner with Fraud Engineering and Data Platform teams to augment data, deploy models, and scale solutions across Ramp’s systems.

Qualifications

• Bachelor’s degree or above in Math, Economics, Physics, CS, or other quantitative field.
• 5+ years of industry experience as ML Engineer, Applied Scientist, or Data Scientist.
• Strong Python experience across ML techniques and backend engineering.
• Experience deploying ML models to production and contributing to backend systems.
• Strong knowledge of SQL (Snowflake, Postgres, etc.).
• Fluency with agentic AI tools for software development and data analysis.

Responsibilities

• Develop core ML models and rules-based systems to detect fraud and abuse.
• Prototype and productionize ML models to protect Ramp and users.
• Collaborate with Fraud Engineering and Data Platform teams to leverage data from multiple sources.
• Influence processes, tools, and systems to improve scalable decision making.

Skills

Python

SQL

ML engineering

Production ML

Data analysis

Education

Bachelor's degree or above in quantitative field

Tools

Snowflake

PostgreSQL

Numpy/Pandas/Sklearn/PyTorch

Job description

Ramp seeks a leader to drive the future of fraud machine learning. You will design data architectures, build core ML models, and set strategic roadmaps to mitigate fraud while minimizing friction for legitimate users.

You will work closely with product and engineering on model design, implementation, execution, and analysis. You will partner with Fraud Engineering and Data Platform teams to augment data, deploy models, and scale solutions across Ramp’s systems.