Ramp - Machine Learning Engineer

New York City, NY, USA$200k - $330k+ Equity3w ago

In Office Senior NA Insurance Payments Machine Learning Engineer Applied Scientist Snowflake SQL Pandas Python Data Analysis

Requirements

• Bachelor’s degree or above in Math, Economics, Physics, Computer Science, or other quantitative fields • A minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist • Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and backend engineering • Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems • Strong knowledge of SQL (Snowflake, Postgres, etc.) • Fluency with agentic (AI) tools for software development and data analysis • Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions • Nice-to-Haves • Nice-to-Haves • PhD in Math, Economics, Physics, Computer Science, or other quantitative fields • Context on Fraud and/or Identity Threat detection systems • Experience with the modern data stack ( Snowflake / Hex / dbt / RisingWave / etc ) • Strong perspective on data science + ML engineering development cycle, especially in a post-AI setting • Experience developing LLM-backed systems or tools • Benefits available to all full-time Ramp employees (Global) • Centralized home-office equipment ordering • Health and wellness stipend • Budget for intra-office travel • Weekly coffee stipend • United States • United States • 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents • One Medical annual membership • 401(k), including employer match on contributions made while employed by Ramp • Fertility HRA (up to $10,000 per year) • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay • In-office perks: lunch, snacks, drinks, and more • Relocation expense coverage to NYC or SF (if needed) • Canada • Canada • Group medical, dental, and vision coverage through Sun Life • Life, AD&D, and disability coverage • Fertility drug coverage (up to $4,000 lifetime) • Group Retirement Plan with employer match (RRSP + DPSP) • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay • Employee Assistance Program and virtual care through Lumino Health • United Kingdom • United Kingdom • Private medical insurance through Freedom Elite • Virtual GP and at-home care via eMed x Livi • Workplace pension through Penfold, with salary sacrifice option • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay • Referral Instructions • If you are being referred for the role, please contact that person to apply on your behalf. • Other notices • Other notices • Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. • Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process. • Ramp Applicant Privacy Notice

Responsibilities

• Employ statistical and machine learning techniques on large datasets to discover patterns of fraud, platform abuse, and identity theft • Prototype and productionize machine learning models and rules-based systems to protect Ramp and its users from fraud • Partner closely with Fraud Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make • Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way

Benefits

• Estimated Base Salary $200K – $330K • Offers Equity • The final compensation will depend on the location and level at which the candidate is hired. • Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. • The problems are high-stakes, data-dense, and unforgiving. • We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. • The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. • If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. • We’re seeking someone to lead the future of fraud machine learning at Ramp. In this role, you will help build core machine learning models, design data architectures, and set strategic roadmaps to help Ramp mitigate fraud-related threats while minimizing the friction experience by legitimate users. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis.