Assistant Machine Learning Engineer

Combining corporate cards with expense management, bill payments, vendor management, accounting automation, and more, Ramp's all-in-one solution frees finance teams to do the best work of their lives. More than 25,000 companies, from family-owned farms to e-commerce giants to space startups, have saved $1B and 10M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over 35 billion dollars in purchases each year.

Ramp's investors include Sequoia, Founders Fund, Thrive Capital, Khosla Ventures, Greylock, Stripe, Goldman Sachs, Coatue, and Redpoint, as well as over 100 angel investors who were founders or executives of leading companies. The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.

We’re seeking someone to lead the future of identity machine learning at Ramp. In this role, you will help build core machine learning, design data architectures, and set strategic roadmaps to help Ramp reduce Identity-related threats. You will partner closely with product and engineering counterparts across model design, implementation, execution, and analysis. Employ statistical and machine learning on large datasets to discover patterns of account takeovers and identity theft

Prototype and productionalize machine learning models and rules-based systems to protect user accounts

Partner closely with Identity 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

Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with 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 back end engineering

Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems

Strong knowledge of SQL (preferably Snowflake, BigQuery)

Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

Context on Fraud and/or Identity Threat detection systems

Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents)

Strong perspective on data science engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)

based full-time employees)

• 100% medical, dental & vision insurance coverage for you
• Flexible PTO
• WFH stipend to support your home office needs
• Parental Leave
• Relocation support to NYC or SF
• 185K – $315K • Offers Equity