Ramp
Machine Learning Engineer
$200K–$330K
New York, NY (HQ) +1 · Hybrid · Full-time · Posted Sep 23, 2026
- Location
- New York, NY (HQ)
Remote (US) - Experience
- Minimum 5 years of industry experience as a Machine Learning Engineer, Applied Scientist, or Data Scientist.
- Education
- Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields.
About the job
Leads development of fraud machine-learning models and data architecture to detect fraud, platform abuse, and identity theft while reducing friction for legitimate users.
What you'll do
- Use statistical and machine-learning techniques on large datasets to identify fraud patterns.
- Prototype and productionize machine-learning models and rules-based fraud-protection systems.
- Partner with Fraud Engineering and Data Platform teams to enrich decision-making data and improve scalable team processes and tools.
What they ask for
- Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or another quantitative field.
- Strong Python experience across ML techniques and backend engineering.
- Experience deploying machine-learning models to production and contributing meaningfully to backend systems.
- Strong SQL knowledge and fluency with agentic AI tools for software development and data analysis.
Nice to have
- PhD in a quantitative field; context on fraud or identity-threat detection systems.
- Experience with the modern data stack or developing LLM-backed systems or tools.
Pay
$200K – $330K (base salary)
Tools
Python, numpy, pandas, sklearn, pytorch, SQL, Snowflake, Postgres
AI focus
Build machine-learning models and rules-based systems for fraud detection and prevention; use agentic AI tools for software development and data analysis. LLM-backed systems or tools are a preferred area of experience.
Model-written summary · the original posting is authoritative